Tunneling in hydrogen-transfer isomerization of n-alkyl radicals.

PubMed

Sirjean, Baptiste; Dames, Enoch; Wang, Hai; Tsang, Wing

2012-01-12

The role of quantum tunneling in hydrogen shift in linear heptyl radicals is explored using multidimensional, small-curvature tunneling method for the transmission coefficients and a potential energy surface computed at the CBS-QB3 level of theory. Several one-dimensional approximations (Wigner, Skodje and Truhlar, and Eckart methods) were compared to the multidimensional results. The Eckart method was found to be sufficiently accurate in comparison to the small-curvature tunneling results for a wide range of temperature, but this agreement is in fact fortuitous and caused by error cancellations. High-pressure limit rate constants were calculated using the transition state theory with treatment of hindered rotations and Eckart transmission coefficients for all hydrogen-transfer isomerizations in n-pentyl to n-octyl radicals. Rate constants are found in good agreement with experimental kinetic data available for n-pentyl and n-hexyl radicals. In the case of n-heptyl and n-octyl, our calculated rates agree well with limited experimentally derived data. Several conclusions made in the experimental studies of Tsang et al. (Tsang, W.; McGivern, W. S.; Manion, J. A. Proc. Combust. Inst. 2009, 32, 131-138) are confirmed theoretically: older low-temperature experimental data, characterized by small pre-exponential factors and activation energies, can be reconciled with high-temperature data by taking into account tunneling; at low temperatures, transmission coefficients are substantially larger for H-atom transfers through a five-membered ring transition state than those with six-membered rings; channels with transition ring structures involving greater than 8 atoms can be neglected because of entropic effects that inhibit such transitions. The set of computational kinetic rates were used to derive a general rate rule that explicitly accounts for tunneling. The rate rule is shown to reproduce closely the theoretical rate constants.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marinov, N.M.; Westbrook, C.K.; Cloutman, L.D.

Work being carried out at LLNL has concentrated on studies of the role of chemical kinetics in a variety of problems related to hydrogen combustion in practical combustion systems, with an emphasis on vehicle propulsion. Use of hydrogen offers significant advantages over fossil fuels, and computer modeling provides advantages when used in concert with experimental studies. Many numerical {open_quotes}experiments{close_quotes} can be carried out quickly and efficiently, reducing the cost and time of system development, and many new and speculative concepts can be screened to identify those with sufficient promise to pursue experimentally. This project uses chemical kinetic and fluid dynamicmore » computational modeling to examine the combustion characteristics of systems burning hydrogen, either as the only fuel or mixed with natural gas. Oxidation kinetics are combined with pollutant formation kinetics, including formation of oxides of nitrogen but also including air toxics in natural gas combustion. We have refined many of the elementary kinetic reaction steps in the detailed reaction mechanism for hydrogen oxidation. To extend the model to pressures characteristic of internal combustion engines, it was necessary to apply theoretical pressure falloff formalisms for several key steps in the reaction mechanism. We have continued development of simplified reaction mechanisms for hydrogen oxidation, we have implemented those mechanisms into multidimensional computational fluid dynamics models, and we have used models of chemistry and fluid dynamics to address selected application problems. At the present time, we are using computed high pressure flame, and auto-ignition data to further refine the simplified kinetics models that are then to be used in multidimensional fluid mechanics models. Detailed kinetics studies have investigated hydrogen flames and ignition of hydrogen behind shock waves, intended to refine the detailed reactions mechanisms.« less

A Gas-Kinetic Scheme for Multimaterial Flows and Its Application in Chemical Reaction

NASA Technical Reports Server (NTRS)

Lian, Yongsheng; Xu, Kun

1999-01-01

This paper concerns the extension of the multicomponent gas-kinetic BGK-type scheme to multidimensional chemical reactive flow calculations. In the kinetic model, each component satisfies its individual gas-kinetic BGK equation and the equilibrium states of both components are coupled in space and time due to the momentum and energy exchange in the course of particle collisions. At the same time, according to the chemical reaction rule one component can be changed into another component with the release of energy, where the reactant and product could have different gamma. Many numerical test cases are included in this paper, which show the robustness and accuracy of kinetic approach in the description of multicomponent reactive flows.

Kinetic model for multidimensional opinion formation

NASA Astrophysics Data System (ADS)

Boudin, Laurent; Monaco, Roberto; Salvarani, Francesco

2010-03-01

In this paper, we deal with a kinetic model to describe the evolution of the opinion in a closed group with respect to a choice between multiple options (e.g., political parties), which takes into account two main mechanisms of opinion formation, namely, the interaction between individuals and the effect of the mass media. We numerically test the model in some relevant cases and eventually provide an existence and a uniqueness result for it.

Investigating fast enzyme-DNA kinetics using multidimensional fluorescence imaging and microfluidics

NASA Astrophysics Data System (ADS)

Robinson, Tom; Manning, Hugh B.; Dunsby, Christopher; Neil, Mark A. A.; Baldwin, Geoff S.; de Mello, Andrew J.; French, Paul M. W.

2010-02-01

We have developed a rapid microfluidic mixing device to image fast kinetics. To verify the performance of the device it was simulated using computational fluid dynamics (CFD) and the results were directly compared to experimental fluorescence lifetime imaging (FLIM) measurements. The theoretical and measured mixing times of the device were found to be in agreement over a range of flow rates. This mixing device is being developed with the aim of analysing fast enzyme kinetics in the sub-millisecond time domain, which cannot be achieved with conventional macro-stopped flow devices. Here we have studied the binding of a DNA repair enzyme, uracil DNA glycosylase (UDG), to a fluorescently labelled DNA substrate. Bulk phase fluorescence measurements have been used to measure changes on binding: it was found that the fluorescence lifetime increased along with an increase in the polarisation anisotropy and rotational correlation time. Analysis of the same reaction in the microfluidic mixer by CFD enabled us to predict the mixing time of the device to be 46 μs, more than 20 times faster than current stopped-flow techniques. We also demonstrate that it is possible to image UDG-DNA interactions within the micromixer using the signal changes observed from the multidimensional spectrofluorometer.

Kinetic study on the H + SiH4 abstraction reaction using an ab initio potential energy surface.

PubMed

Cao, Jianwei; Zhang, Zhijun; Zhang, Chunfang; Bian, Wensheng; Guo, Yin

2011-01-14

Variational transition state theory calculations with the correction of multidimensional tunneling are performed on a 12-dimensional ab initio potential energy surface for the H + SiH(4) abstraction reaction. The surface is constructed using a dual-level strategy. For the temperature range 200-1600 K, thermal rate constants are calculated and kinetic isotope effects for various isotopic species of the title reaction are investigated. The results are in very good agreement with available experimental data.

A Comparative Study of Online Item Calibration Methods in Multidimensional Computerized Adaptive Testing

ERIC Educational Resources Information Center

Chen, Ping

2017-01-01

Calibration of new items online has been an important topic in item replenishment for multidimensional computerized adaptive testing (MCAT). Several online calibration methods have been proposed for MCAT, such as multidimensional "one expectation-maximization (EM) cycle" (M-OEM) and multidimensional "multiple EM cycles"…

The Tunneling Method for Global Optimization in Multidimensional Scaling.

ERIC Educational Resources Information Center

Groenen, Patrick J. F.; Heiser, Willem J.

1996-01-01

A tunneling method for global minimization in multidimensional scaling is introduced and adjusted for multidimensional scaling with general Minkowski distances. The method alternates a local search step with a tunneling step in which a different configuration is sought with the same STRESS implementation. (SLD)

Multi-fluid CFD analysis in Process Engineering

NASA Astrophysics Data System (ADS)

Hjertager, B. H.

2017-12-01

An overview of modelling and simulation of flow processes in gas/particle and gas/liquid systems are presented. Particular emphasis is given to computational fluid dynamics (CFD) models that use the multi-dimensional multi-fluid techniques. Turbulence modelling strategies for gas/particle flows based on the kinetic theory for granular flows are given. Sub models for the interfacial transfer processes and chemical kinetics modelling are presented. Examples are shown for some gas/particle systems including flow and chemical reaction in risers as well as gas/liquid systems including bubble columns and stirred tanks.

Towards the identification of Idiopathic Parkinson’s Disease from the speech. New articulatory kinetic biomarkers

PubMed Central

Shattuck-Hufnagel, S.; Choi, J. Y.; Moro-Velázquez, L.; Gómez-García, J. A.

2017-01-01

Although a large amount of acoustic indicators have already been proposed in the literature to evaluate the hypokinetic dysarthria of people with Parkinson’s Disease, the goal of this work is to identify and interpret new reliable and complementary articulatory biomarkers that could be applied to predict/evaluate Parkinson’s Disease from a diadochokinetic test, contributing to the possibility of a further multidimensional analysis of the speech of parkinsonian patients. The new biomarkers proposed are based on the kinetic behaviour of the envelope trace, which is directly linked with the articulatory dysfunctions introduced by the disease since the early stages. The interest of these new articulatory indicators stands on their easiness of identification and interpretation, and their potential to be translated into computer based automatic methods to screen the disease from the speech. Throughout this paper, the accuracy provided by these acoustic kinetic biomarkers is compared with the one obtained with a baseline system based on speaker identification techniques. Results show accuracies around 85% that are in line with those obtained with the complex state of the art speaker recognition techniques, but with an easier physical interpretation, which open the possibility to be transferred to a clinical setting. PMID:29240814

Nuclear quantum effects and kinetic isotope effects in enzyme reactions.

PubMed

Vardi-Kilshtain, Alexandra; Nitoker, Neta; Major, Dan Thomas

2015-09-15

Enzymes are extraordinarily effective catalysts evolved to perform well-defined and highly specific chemical transformations. Studying the nature of rate enhancements and the mechanistic strategies in enzymes is very important, both from a basic scientific point of view, as well as in order to improve rational design of biomimetics. Kinetic isotope effect (KIE) is a very important tool in the study of chemical reactions and has been used extensively in the field of enzymology. Theoretically, the prediction of KIEs in condensed phase environments such as enzymes is challenging due to the need to include nuclear quantum effects (NQEs). Herein we describe recent progress in our group in the development of multi-scale simulation methods for the calculation of NQEs and accurate computation of KIEs. We also describe their application to several enzyme systems. In particular we describe the use of combined quantum mechanics/molecular mechanics (QM/MM) methods in classical and quantum simulations. The development of various novel path-integral methods is reviewed. These methods are tailor suited to enzyme systems, where only a few degrees of freedom involved in the chemistry need to be quantized. The application of the hybrid QM/MM quantum-classical simulation approach to three case studies is presented. The first case involves the proton transfer in alanine racemase. The second case presented involves orotidine 5'-monophosphate decarboxylase where multidimensional free energy simulations together with kinetic isotope effects are combined in the study of the reaction mechanism. Finally, we discuss the proton transfer in nitroalkane oxidase, where the enzyme employs tunneling as a catalytic fine-tuning tool. Copyright © 2015 Elsevier Inc. All rights reserved.

Nucleation barrier reconstruction via the seeding method in a lattice model with competing nucleation pathways.

PubMed

Lifanov, Yuri; Vorselaars, Bart; Quigley, David

2016-12-07

We study a three-species analogue of the Potts lattice gas model of nucleation from solution in a regime where partially disordered solute is a viable thermodynamic phase. Using a multicanonical sampling protocol, we compute phase diagrams for the system, from which we determine a parameter regime where the partially disordered phase is metastable almost everywhere in the temperature-fugacity plane. The resulting model shows non-trivial nucleation and growth behaviour, which we examine via multidimensional free energy calculations. We consider the applicability of the model in capturing the multi-stage nucleation mechanisms of polymorphic biominerals (e.g., CaCO 3 ). We then quantitatively explore the kinetics of nucleation in our model using the increasingly popular "seeding" method. We compare the resulting free energy barrier heights to those obtained via explicit free energy calculations over a wide range of temperatures and fugacities, carefully considering the propagation of statistical error. We find that the ability of the "seeding" method to reproduce accurate free energy barriers is dependent on the degree of supersaturation, and severely limited by the use of a nucleation driving force Δμ computed for bulk phases. We discuss possible reasons for this in terms of underlying kinetic assumptions, and those of classical nucleation theory.

Multidimensional spectrometer

DOEpatents

Zanni, Martin Thomas; Damrauer, Niels H.

2010-07-20

A multidimensional spectrometer for the infrared, visible, and ultraviolet regions of the electromagnetic spectrum, and a method for making multidimensional spectroscopic measurements in the infrared, visible, and ultraviolet regions of the electromagnetic spectrum. The multidimensional spectrometer facilitates measurements of inter- and intra-molecular interactions.

Multidimensional upwind hydrodynamics on unstructured meshes using graphics processing units - I. Two-dimensional uniform meshes

NASA Astrophysics Data System (ADS)

Paardekooper, S.-J.

2017-08-01

We present a new method for numerical hydrodynamics which uses a multidimensional generalization of the Roe solver and operates on an unstructured triangular mesh. The main advantage over traditional methods based on Riemann solvers, which commonly use one-dimensional flux estimates as building blocks for a multidimensional integration, is its inherently multidimensional nature, and as a consequence its ability to recognize multidimensional stationary states that are not hydrostatic. A second novelty is the focus on graphics processing units (GPUs). By tailoring the algorithms specifically to GPUs, we are able to get speedups of 100-250 compared to a desktop machine. We compare the multidimensional upwind scheme to a traditional, dimensionally split implementation of the Roe solver on several test problems, and we find that the new method significantly outperforms the Roe solver in almost all cases. This comes with increased computational costs per time-step, which makes the new method approximately a factor of 2 slower than a dimensionally split scheme acting on a structured grid.

tICA-Metadynamics: Accelerating Metadynamics by Using Kinetically Selected Collective Variables.

PubMed

M Sultan, Mohammad; Pande, Vijay S

2017-06-13

Metadynamics is a powerful enhanced molecular dynamics sampling method that accelerates simulations by adding history-dependent multidimensional Gaussians along selective collective variables (CVs). In practice, choosing a small number of slow CVs remains challenging due to the inherent high dimensionality of biophysical systems. Here we show that time-structure based independent component analysis (tICA), a recent advance in Markov state model literature, can be used to identify a set of variationally optimal slow coordinates for use as CVs for Metadynamics. We show that linear and nonlinear tICA-Metadynamics can complement existing MD studies by explicitly sampling the system's slowest modes and can even drive transitions along the slowest modes even when no such transitions are observed in unbiased simulations.

The Efficacy of Multidimensional Constraint Keys in Database Query Performance

ERIC Educational Resources Information Center

Cardwell, Leslie K.

2012-01-01

This work is intended to introduce a database design method to resolve the two-dimensional complexities inherent in the relational data model and its resulting performance challenges through abstract multidimensional constructs. A multidimensional constraint is derived and utilized to implement an indexed Multidimensional Key (MK) to abstract a…

Theoretical studies for the rates and kinetic isotope effects of the excited-state double proton transfer in the 1:1 7-azaindole:H2O complex using variational transition state theory including multidimensional tunneling.

PubMed

Duong, My Phu Thi; Kim, Yongho

2010-03-18

Variational transition state theory calculations including multidimensional tunneling (VTST/MT) for excited-state tautomerization in the 1:1 7-azaindole:H(2)O complex were performed. Electronic structures and energies for reactant, product, transition state, and potential energy curves along the reaction coordinate were computed at the CASSCF(10,9)/6-31G(d,p) level of theory. The potential energies were corrected by second-order multireference perturbation theory to take the dynamic electron correlation into consideration. The final potential energy curves along the reaction coordinate were generated at the MRPT2//CASSCF(10,9)/6-31G(d,p) level. Two protons in the excited-state tautomerization are transferred concertedly, albeit asynchronously. The position of the variational transition state is very different from the conventional transition state, and is highly dependent on isotopic substitution. Rate constants were calculated using VTST/MT, and were on the order of 10(-6) s(-1) at room temperature. The HH/DD kinetic isotope effects are consistent with experimental observations; consideration of both tunneling and variational effects was essential to predict the experimental values correctly.

Kinetics of enzymatic high-solid hydrolysis of lignocellulosic biomass studied by calorimetry.

PubMed

Olsen, Søren N; Lumby, Erik; McFarland, Kc; Borch, Kim; Westh, Peter

2011-03-01

Enzymatic hydrolysis of high-solid biomass (>10% w/w dry mass) has become increasingly important as a key step in the production of second-generation bioethanol. To this end, development of quantitative real-time assays is desirable both for empirical optimization and for detailed kinetic analysis. In the current work, we have investigated the application of isothermal calorimetry to study the kinetics of enzymatic hydrolysis of two substrates (pretreated corn stover and Avicel) at high-solid contents (up to 29% w/w). It was found that the calorimetric heat flow provided a true measure of the hydrolysis rate with a detection limit of about 500 pmol glucose s(-1). Hence, calorimetry is shown to be a highly sensitive real-time method, applicable for high solids, and independent on the complexity of the substrate. Dose-response experiments with a typical cellulase cocktail enabled a multidimensional analysis of the interrelationships of enzyme load and the rate, time, and extent of the reaction. The results suggest that the hydrolysis rate of pretreated corn stover is limited initially by available attack points on the substrate surface (<10% conversion) but becomes proportional to enzyme dosage (excess of attack points) at later stages (>10% conversion). This kinetic profile is interpreted as an increase in polymer end concentration (substrate for CBH) as the hydrolysis progresses, probably due to EG activity in the enzyme cocktail. Finally, irreversible enzyme inactivation did not appear to be the source of reduced hydrolysis rate over time.

Application of kinetic flux vector splitting scheme for solving multi-dimensional hydrodynamical models of semiconductor devices

NASA Astrophysics Data System (ADS)

Nisar, Ubaid Ahmed; Ashraf, Waqas; Qamar, Shamsul

In this article, one and two-dimensional hydrodynamical models of semiconductor devices are numerically investigated. The models treat the propagation of electrons in a semiconductor device as the flow of a charged compressible fluid. It plays an important role in predicting the behavior of electron flow in semiconductor devices. Mathematically, the governing equations form a convection-diffusion type system with a right hand side describing the relaxation effects and interaction with a self consistent electric field. The proposed numerical scheme is a splitting scheme based on the kinetic flux-vector splitting (KFVS) method for the hyperbolic step, and a semi-implicit Runge-Kutta method for the relaxation step. The KFVS method is based on the direct splitting of macroscopic flux functions of the system on the cell interfaces. The second order accuracy of the scheme is achieved by using MUSCL-type initial reconstruction and Runge-Kutta time stepping method. Several case studies are considered. For validation, the results of current scheme are compared with those obtained from the splitting scheme based on the NT central scheme. The effects of various parameters such as low field mobility, device length, lattice temperature and voltage are analyzed. The accuracy, efficiency and simplicity of the proposed KFVS scheme validates its generic applicability to the given model equations. A two dimensional simulation is also performed by KFVS method for a MESFET device, producing results in good agreement with those obtained by NT-central scheme.

Multidimensional Programming Methods for Energy Facility Siting: Alternative Approaches

NASA Technical Reports Server (NTRS)

Solomon, B. D.; Haynes, K. E.

1982-01-01

The use of multidimensional optimization methods in solving power plant siting problems, which are characterized by several conflicting, noncommensurable objectives is addressed. After a discussion of data requirements and exclusionary site screening methods for bounding the decision space, classes of multiobjective and goal programming models are discussed in the context of finite site selection. Advantages and limitations of these approaches are highlighted and the linkage of multidimensional methods with the subjective, behavioral components of the power plant siting process is emphasized.

GENERAL: Scattering Phase Correction for Semiclassical Quantization Rules in Multi-Dimensional Quantum Systems

NASA Astrophysics Data System (ADS)

Huang, Wen-Min; Mou, Chung-Yu; Chang, Cheng-Hung

2010-02-01

While the scattering phase for several one-dimensional potentials can be exactly derived, less is known in multi-dimensional quantum systems. This work provides a method to extend the one-dimensional phase knowledge to multi-dimensional quantization rules. The extension is illustrated in the example of Bogomolny's transfer operator method applied in two quantum wells bounded by step potentials of different heights. This generalized semiclassical method accurately determines the energy spectrum of the systems, which indicates the substantial role of the proposed phase correction. Theoretically, the result can be extended to other semiclassical methods, such as Gutzwiller trace formula, dynamical zeta functions, and semiclassical Landauer-Büttiker formula. In practice, this recipe enhances the applicability of semiclassical methods to multi-dimensional quantum systems bounded by general soft potentials.

Monte Carlo method for computing density of states and quench probability of potential energy and enthalpy landscapes.

PubMed

Mauro, John C; Loucks, Roger J; Balakrishnan, Jitendra; Raghavan, Srikanth

2007-05-21

The thermodynamics and kinetics of a many-body system can be described in terms of a potential energy landscape in multidimensional configuration space. The partition function of such a landscape can be written in terms of a density of states, which can be computed using a variety of Monte Carlo techniques. In this paper, a new self-consistent Monte Carlo method for computing density of states is described that uses importance sampling and a multiplicative update factor to achieve rapid convergence. The technique is then applied to compute the equilibrium quench probability of the various inherent structures (minima) in the landscape. The quench probability depends on both the potential energy of the inherent structure and the volume of its corresponding basin in configuration space. Finally, the methodology is extended to the isothermal-isobaric ensemble in order to compute inherent structure quench probabilities in an enthalpy landscape.

Method of data mining including determining multidimensional coordinates of each item using a predetermined scalar similarity value for each item pair

DOEpatents

Meyers, Charles E.; Davidson, George S.; Johnson, David K.; Hendrickson, Bruce A.; Wylie, Brian N.

1999-01-01

A method of data mining represents related items in a multidimensional space. Distance between items in the multidimensional space corresponds to the extent of relationship between the items. The user can select portions of the space to perceive. The user also can interact with and control the communication of the space, focusing attention on aspects of the space of most interest. The multidimensional spatial representation allows more ready comprehension of the structure of the relationships among the items.

Nonlinear Conservation Laws and Finite Volume Methods

NASA Astrophysics Data System (ADS)

Leveque, Randall J.

Introduction Software Notation Classification of Differential Equations Derivation of Conservation Laws The Euler Equations of Gas Dynamics Dissipative Fluxes Source Terms Radiative Transfer and Isothermal Equations Multi-dimensional Conservation Laws The Shock Tube Problem Mathematical Theory of Hyperbolic Systems Scalar Equations Linear Hyperbolic Systems Nonlinear Systems The Riemann Problem for the Euler Equations Numerical Methods in One Dimension Finite Difference Theory Finite Volume Methods Importance of Conservation Form - Incorrect Shock Speeds Numerical Flux Functions Godunov's Method Approximate Riemann Solvers High-Resolution Methods Other Approaches Boundary Conditions Source Terms and Fractional Steps Unsplit Methods Fractional Step Methods General Formulation of Fractional Step Methods Stiff Source Terms Quasi-stationary Flow and Gravity Multi-dimensional Problems Dimensional Splitting Multi-dimensional Finite Volume Methods Grids and Adaptive Refinement Computational Difficulties Low-Density Flows Discrete Shocks and Viscous Profiles Start-Up Errors Wall Heating Slow-Moving Shocks Grid Orientation Effects Grid-Aligned Shocks Magnetohydrodynamics The MHD Equations One-Dimensional MHD Solving the Riemann Problem Nonstrict Hyperbolicity Stiffness The Divergence of B Riemann Problems in Multi-dimensional MHD Staggered Grids The 8-Wave Riemann Solver Relativistic Hydrodynamics Conservation Laws in Spacetime The Continuity Equation The 4-Momentum of a Particle The Stress-Energy Tensor Finite Volume Methods Multi-dimensional Relativistic Flow Gravitation and General Relativity References

Best Design for Multidimensional Computerized Adaptive Testing With the Bifactor Model

PubMed Central

Seo, Dong Gi; Weiss, David J.

2015-01-01

Most computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm (MCAT) with a bifactor model using simulated data. Four item selection methods in MCAT were examined for three bifactor pattern designs using two multidimensional item response theory models. To compare MCAT item selection and estimation methods, a fixed test length was used. The Ds-optimality item selection improved θ estimates with respect to a general factor, and either D- or A-optimality improved estimates of the group factors in three bifactor pattern designs under two multidimensional item response theory models. The MCAT model without a guessing parameter functioned better than the MCAT model with a guessing parameter. The MAP (maximum a posteriori) estimation method provided more accurate θ estimates than the EAP (expected a posteriori) method under most conditions, and MAP showed lower observed standard errors than EAP under most conditions, except for a general factor condition using Ds-optimality item selection. PMID:29795848

Controlling specific locomotor behaviors through multidimensional monoaminergic modulation of spinal circuitries

PubMed Central

Musienko, Pavel; van den Brand, Rubia; Märzendorfer, Olivia; Roy, Roland R.; Gerasimenko, Yury; Edgerton, V. Reggie; Courtine, Grégoire

2012-01-01

Descending monoaminergic inputs markedly influence spinal locomotor circuits, but the functional relationships between specific receptors and the control of walking behavior remain poorly understood. To identify these interactions, we manipulated serotonergic, dopaminergic, and noradrenergic neural pathways pharmacologically during locomotion enabled by electrical spinal cord stimulation in adult spinal rats in vivo. Using advanced neurobiomechanical recordings and multidimensional statistical procedures, we reveal that each monoaminergic receptor modulates a broad but distinct spectrum of kinematic, kinetic and EMG characteristics, which we expressed into receptor–specific functional maps. We then exploited this catalogue of monoaminergic tuning functions to devise optimal pharmacological combinations to encourage locomotion in paralyzed rats. We found that, in most cases, receptor-specific modulatory influences summed near algebraically when stimulating multiple pathways concurrently. Capitalizing on these predictive interactions, we elaborated a multidimensional monoaminergic intervention that restored coordinated hindlimb locomotion with normal levels of weight bearing and partial equilibrium maintenance in spinal rats. These findings provide new perspectives on the functions of and interactions between spinal monoaminergic receptor systems in producing stepping, and define a framework to tailor pharmacotherapies for improving neurological functions after CNS disorders. PMID:21697376

Imaging a multidimensional multichannel potential energy surface: Photodetachment of H(-)(NH3) and NH4 (.).

PubMed

Hu, Qichi; Song, Hongwei; Johnson, Christopher J; Li, Jun; Guo, Hua; Continetti, Robert E

2016-06-28

Probes of the Born-Oppenheimer potential energy surfaces governing polyatomic molecules often rely on spectroscopy for the bound regions or collision experiments in the continuum. A combined spectroscopic and half-collision approach to image nuclear dynamics in a multidimensional and multichannel system is reported here. The Rydberg radical NH4 and the double Rydberg anion NH4 (-) represent a polyatomic system for benchmarking electronic structure and nine-dimensional quantum dynamics calculations. Photodetachment of the H(-)(NH3) ion-dipole complex and the NH4 (-) DRA probes different regions on the neutral NH4 PES. Photoelectron energy and angular distributions at photon energies of 1.17, 1.60, and 2.33 eV compare well with quantum dynamics. Photoelectron-photofragment coincidence experiments indicate dissociation of the nascent NH4 Rydberg radical occurs to H + NH3 with a peak kinetic energy of 0.13 eV, showing the ground state of NH4 to be unstable, decaying by tunneling-induced dissociation on a time scale beyond the present scope of multidimensional quantum dynamics.

Biofuel combustion. Energetics and kinetics of hydrogen abstraction from carbon-1 in n-butanol by the hydroperoxyl radical calculated by coupled cluster and density functional theories and multistructural variational transition-state theory with multidimensional tunneling.

PubMed

Alecu, I M; Zheng, Jingjing; Papajak, Ewa; Yu, Tao; Truhlar, Donald G

2012-12-20

Multistructural canonical variational transition-state theory with small-curvature multidimensional tunneling (MS-CVT/SCT) is employed to calculate thermal rate constants for hydrogen-atom abstraction from carbon-1 of n-butanol by the hydroperoxyl radical over the temperature range 250-2000 K. The M08-SO hybrid meta-GGA density functional was validated against CCSD(T)-F12a explicitly correlated wave function calculations with the jul-cc-pVTZ basis set. It was then used to compute the properties of all stationary points and the energies and Hessians of a few nonstationary points along the reaction path, which were then used to generate a potential energy surface by the multiconfiguration Shepard interpolation (MCSI) method. The internal rotations in the transition state for this reaction (like those in the reactant alcohol) are strongly coupled to each other and generate multiple stable conformations, which make important contributions to the partition functions. It is shown that neglecting to account for the multiple-structure effects and torsional potential anharmonicity effects that arise from the torsional modes would lead to order-of-magnitude errors in the calculated rate constants at temperatures of interest in combustion.

A New Time-varying Concept of Risk in a Changing Climate.

PubMed

Sarhadi, Ali; Ausín, María Concepción; Wiper, Michael P

2016-10-20

In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments.

Zero-point angular momentum of supersymmetric Penning trap

NASA Astrophysics Data System (ADS)

Zhang, Jian-zu; Xu, Qiang

2000-10-01

The quantum behavior of supersymmetric Penning trap, specially the superpartner of its angular momentum, is investigated in the formulation of multi-dimensional semiunitary transformation of supersymmetric quantum mechanics. In the limit case of vanishing kinetic energy it is found that its lowest angular momentum is 3ℏ/2, which provides a possibility of directly checking the idea of supersymmetric quantum mechanics and thus suggests a possible experimental verification about this prediction.

Stereodynamical Origin of Anti-Arrhenius Kinetics: Negative Activation Energy and Roaming for a Four-Atom Reaction.

PubMed

Coutinho, Nayara D; Silva, Valter H C; de Oliveira, Heibbe C B; Camargo, Ademir J; Mundim, Kleber C; Aquilanti, Vincenzo

2015-05-07

The OH + HBr → H2O + Br reaction, prototypical of halogen-atom liberating processes relevant to mechanisms for atmospheric ozone destruction, attracted frequent attention of experimental chemical kinetics: the nature of the unusual reactivity drop from low to high temperatures eluded a variety of theoretical efforts, ranking this one among the most studied four-atom reactions. Here, inspired by oriented molecular-beams experiments, we develop a first-principles stereodynamical approach. Thermalized sets of trajectories, evolving on a multidimensional potential energy surface quantum mechanically generated on-the-fly, provide a map of most visited regions at each temperature. Visualizations of rearrangements of bonds along trajectories and of the role of specific angles of reactants' mutual approach elucidate the mechanistic change from the low kinetic energy regime (where incident reactants reorient to find the propitious alignment leading to reaction) to high temperature (where speed hinders adjustment of directionality and roaming delays reactivity).

A family of high-order gas-kinetic schemes and its comparison with Riemann solver based high-order methods

NASA Astrophysics Data System (ADS)

Ji, Xing; Zhao, Fengxiang; Shyy, Wei; Xu, Kun

2018-03-01

Most high order computational fluid dynamics (CFD) methods for compressible flows are based on Riemann solver for the flux evaluation and Runge-Kutta (RK) time stepping technique for temporal accuracy. The advantage of this kind of space-time separation approach is the easy implementation and stability enhancement by introducing more middle stages. However, the nth-order time accuracy needs no less than n stages for the RK method, which can be very time and memory consuming due to the reconstruction at each stage for a high order method. On the other hand, the multi-stage multi-derivative (MSMD) method can be used to achieve the same order of time accuracy using less middle stages with the use of the time derivatives of the flux function. For traditional Riemann solver based CFD methods, the lack of time derivatives in the flux function prevents its direct implementation of the MSMD method. However, the gas kinetic scheme (GKS) provides such a time accurate evolution model. By combining the second-order or third-order GKS flux functions with the MSMD technique, a family of high order gas kinetic methods can be constructed. As an extension of the previous 2-stage 4th-order GKS, the 5th-order schemes with 2 and 3 stages will be developed in this paper. Based on the same 5th-order WENO reconstruction, the performance of gas kinetic schemes from the 2nd- to the 5th-order time accurate methods will be evaluated. The results show that the 5th-order scheme can achieve the theoretical order of accuracy for the Euler equations, and present accurate Navier-Stokes solutions as well due to the coupling of inviscid and viscous terms in the GKS formulation. In comparison with Riemann solver based 5th-order RK method, the high order GKS has advantages in terms of efficiency, accuracy, and robustness, for all test cases. The 4th- and 5th-order GKS have the same robustness as the 2nd-order scheme for the capturing of discontinuous solutions. The current high order MSMD GKS is a multi-dimensional scheme with incorporation of both normal and tangential spatial derivatives of flow variables at a cell interface in the flux evaluation. The scheme can be extended straightforwardly to viscous flow computation in unstructured mesh. It provides a promising direction for the development of high-order CFD methods for the computation of complex flows, such as turbulence and acoustics with shock interactions.

The Use of the Visualisation of Multidimensional Data Using PCA to Evaluate Possibilities of the Division of Coal Samples Space Due to their Suitability for Fluidised Gasification

NASA Astrophysics Data System (ADS)

Jamróz, Dariusz; Niedoba, Tomasz; Surowiak, Agnieszka; Tumidajski, Tadeusz

2016-09-01

Methods serving to visualise multidimensional data through the transformation of multidimensional space into two-dimensional space, enable to present the multidimensional data on the computer screen. Thanks to this, qualitative analysis of this data can be performed in the most natural way for humans, through the sense of sight. An example of such a method of multidimensional data visualisation is PCA (principal component analysis) method. This method was used in this work to present and analyse a set of seven-dimensional data (selected seven properties) describing coal samples obtained from Janina and Wieczorek coal mines. Coal from these mines was previously subjected to separation by means of a laboratory ring jig, consisting of ten rings. With 5 layers of both types of coal (with 2 rings each) were obtained in this way. It was decided to check if the method of multidimensional data visualisation enables to divide the space of such divided samples into areas with different suitability for the fluidised gasification process. To that end, the card of technological suitability of coal was used (Sobolewski et al., 2012; 2013), in which key, relevant and additional parameters, having effect on the gasification process, were described. As a result of analyses, it was stated that effective determination of coal samples suitability for the on-surface gasification process in a fluidised reactor is possible. The PCA method enables the visualisation of the optimal subspace containing the set requirements concerning the properties of coals intended for this process.

Imaging a multidimensional multichannel potential energy surface: Photodetachment of H{sup −}(NH{sub 3}) and NH{sub 4}{sup −}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Qichi; Johnson, Christopher J.; Continetti, Robert E., E-mail: hguo@umn.edu, E-mail: rcontinetti@ucsd.edu

2016-06-28

Probes of the Born-Oppenheimer potential energy surfaces governing polyatomic molecules often rely on spectroscopy for the bound regions or collision experiments in the continuum. A combined spectroscopic and half-collision approach to image nuclear dynamics in a multidimensional and multichannel system is reported here. The Rydberg radical NH{sub 4} and the double Rydberg anion NH{sub 4}{sup −} represent a polyatomic system for benchmarking electronic structure and nine-dimensional quantum dynamics calculations. Photodetachment of the H{sup −}(NH{sub 3}) ion-dipole complex and the NH{sub 4}{sup −} DRA probes different regions on the neutral NH{sub 4} PES. Photoelectron energy and angular distributions at photon energiesmore » of 1.17, 1.60, and 2.33 eV compare well with quantum dynamics. Photoelectron-photofragment coincidence experiments indicate dissociation of the nascent NH{sub 4} Rydberg radical occurs to H + NH{sub 3} with a peak kinetic energy of 0.13 eV, showing the ground state of NH{sub 4} to be unstable, decaying by tunneling-induced dissociation on a time scale beyond the present scope of multidimensional quantum dynamics.« less

Simulations of Flame Acceleration and Deflagration-to-Detonation Transitions in Methane-Air Systems

DTIC Science & Technology

2010-03-17

are neglected. 3. Model parameter calibration The one-step Arrhenius kinetics used in this model cannot ex- actly reproduce all properties of laminar...with obstacles are compared to previ- ously reported experimental data. The results obtained using the simple reaction model qualitatively, and in...have taken in developing a multidimensional numerical model to study explosions in large-scale systems containing mixtures of nat- ural gas and air

Improving Multidimensional Wireless Sensor Network Lifetime Using Pearson Correlation and Fractal Clustering

PubMed Central

Almeida, Fernando R.; Brayner, Angelo; Rodrigues, Joel J. P. C.; Maia, Jose E. Bessa

2017-01-01

An efficient strategy for reducing message transmission in a wireless sensor network (WSN) is to group sensors by means of an abstraction denoted cluster. The key idea behind the cluster formation process is to identify a set of sensors whose sensed values present some data correlation. Nowadays, sensors are able to simultaneously sense multiple different physical phenomena, yielding in this way multidimensional data. This paper presents three methods for clustering sensors in WSNs whose sensors collect multidimensional data. The proposed approaches implement the concept of multidimensional behavioral clustering. To show the benefits introduced by the proposed methods, a prototype has been implemented and experiments have been carried out on real data. The results prove that the proposed methods decrease the amount of data flowing in the network and present low root-mean-square error (RMSE). PMID:28590450

Improving Multidimensional Wireless Sensor Network Lifetime Using Pearson Correlation and Fractal Clustering.

PubMed

Almeida, Fernando R; Brayner, Angelo; Rodrigues, Joel J P C; Maia, Jose E Bessa

2017-06-07

An efficient strategy for reducing message transmission in a wireless sensor network (WSN) is to group sensors by means of an abstraction denoted cluster. The key idea behind the cluster formation process is to identify a set of sensors whose sensed values present some data correlation. Nowadays, sensors are able to simultaneously sense multiple different physical phenomena, yielding in this way multidimensional data. This paper presents three methods for clustering sensors in WSNs whose sensors collect multidimensional data. The proposed approaches implement the concept of multidimensional behavioral clustering . To show the benefits introduced by the proposed methods, a prototype has been implemented and experiments have been carried out on real data. The results prove that the proposed methods decrease the amount of data flowing in the network and present low root-mean-square error (RMSE).

The Multidimensional Assessment of Interoceptive Awareness (MAIA)

PubMed Central

Mehling, Wolf E.; Price, Cynthia; Daubenmier, Jennifer J.; Acree, Mike; Bartmess, Elizabeth; Stewart, Anita

2012-01-01

This paper describes the development of a multidimensional self-report measure of interoceptive body awareness. The systematic mixed-methods process involved reviewing the current literature, specifying a multidimensional conceptual framework, evaluating prior instruments, developing items, and analyzing focus group responses to scale items by instructors and patients of body awareness-enhancing therapies. Following refinement by cognitive testing, items were field-tested in students and instructors of mind-body approaches. Final item selection was achieved by submitting the field test data to an iterative process using multiple validation methods, including exploratory cluster and confirmatory factor analyses, comparison between known groups, and correlations with established measures of related constructs. The resulting 32-item multidimensional instrument assesses eight concepts. The psychometric properties of these final scales suggest that the Multidimensional Assessment of Interoceptive Awareness (MAIA) may serve as a starting point for research and further collaborative refinement. PMID:23133619

Flexibility, Diversity, and Cooperativity: Pillars of Enzyme Catalysis

PubMed Central

Hammes, Gordon G.; Benkovic, Stephen J.; Hammes-Schiffer, Sharon

2011-01-01

This brief review discusses our current understanding of the molecular basis of enzyme catalysis. A historical development is presented, beginning with steady state kinetics and progressing through modern fast reaction methods, NMR, and single molecule fluorescence techniques. Experimental results are summarized for ribonuclease, aspartate aminotransferase, and especially dihydrofolate reductase (DHFR). Multiple intermediates, multiple conformations, and cooperative conformational changes are shown to be an essential part of virtually all enzyme mechanisms. In the case of DHFR, theoretical investigations have provided detailed information about the movement of atoms within the enzyme-substrate complex as the reaction proceeds along the collective reaction coordinate for hydride transfer. A general mechanism is presented for enzyme catalysis that includes multiple intermediates and a complex, multidimensional standard free energy surface. Protein flexibility, diverse protein conformations, and cooperative conformational changes are important features of this model. PMID:22029278

Observation and explanation of two-dimensional interconversion of oximes with multiple heart-cutting using comprehensive multidimensional gas chromatography.

PubMed

Kulsing, Chadin; Nolvachai, Yada; Wong, Yong Foo; Glouzman, Melissa I; Marriott, Philip J

2018-04-20

Real-time interconversion processes produce unconventional peak broadening in gas chromatography (GC), and can be used to generate kinetic and thermodynamic data. In this study, an unusual separation situation in comprehensive two dimensional GC where two dimensional interconversion (i.e. a raised plateau in both first and second dimension, 1 D and 2 D) was observed in analysis of oxime isomers. This resulted in a characteristic and unusual rectangular peak shape in the two dimensional result. A related theoretical approach was introduced to explain the peak shape supported by simulation results which can be varied depending on concentration profiles and kinetics of the process. The simulated results were supported by experimental results obtained by a comprehensive heart-cut multidimensional GC (H/C MDGC) approach which was developed to clearly investigate isomerisation of E/Z oxime molecules in both 1 D and 2 D separations under different isothermal conditions. The carrier gas flow and oven temperature were selected according to initial results for 1D interconversion on a poly(ethyleneglycol) stationary phase, which was further used in both 1 D and 2 D separations to result in broad zones of oxime interconversion in both dimensions. The method involved repetitive injections of oxime sample, then sampling contiguous fractions of sample into a long 2 D column which is intended to promote considerable interconversion. Comprehensiveness arises from the fact that the whole sample is sampled from the 1 D to the 2 D column, with the long 2 D column replacing the short 2 D column used in classical comprehensive two-dimensional gas chromatography, where the latter will not promote sufficient interconversion. Data processing and presentation permits a 'rectangular' distribution corresponding to the separated compounds, characteristic of this experiment. Copyright © 2018 Elsevier B.V. All rights reserved.

Coupling of TRAC-PF1/MOD2, Version 5.4.25, with NESTLE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Knepper, P.L.; Hochreiter, L.E.; Ivanov, K.N.

1999-09-01

A three-dimensional (3-D) spatial kinetics capability within a thermal-hydraulics system code provides a more correct description of the core physics during reactor transients that involve significant variations in the neutron flux distribution. Coupled codes provide the ability to forecast safety margins in a best-estimate manner. The behavior of a reactor core and the feedback to the plant dynamics can be accurately simulated. For each time step, coupled codes are capable of resolving system interaction effects on neutronics feedback and are capable of describing local neutronics effects caused by the thermal hydraulics and neutronics coupling. With the improvements in computational technology,more » modeling complex reactor behaviors with coupled thermal hydraulics and spatial kinetics is feasible. Previously, reactor analysis codes were limited to either a detailed thermal-hydraulics model with simplified kinetics or multidimensional neutron kinetics with a simplified thermal-hydraulics model. The authors discuss the coupling of the Transient Reactor Analysis Code (TRAC)-PF1/MOD2, Version 5.4.25, with the NESTLE code.« less

A Heterogeneous Network Based Method for Identifying GBM-Related Genes by Integrating Multi-Dimensional Data.

PubMed

Chen Peng; Ao Li

2017-01-01

The emergence of multi-dimensional data offers opportunities for more comprehensive analysis of the molecular characteristics of human diseases and therefore improving diagnosis, treatment, and prevention. In this study, we proposed a heterogeneous network based method by integrating multi-dimensional data (HNMD) to identify GBM-related genes. The novelty of the method lies in that the multi-dimensional data of GBM from TCGA dataset that provide comprehensive information of genes, are combined with protein-protein interactions to construct a weighted heterogeneous network, which reflects both the general and disease-specific relationships between genes. In addition, a propagation algorithm with resistance is introduced to precisely score and rank GBM-related genes. The results of comprehensive performance evaluation show that the proposed method significantly outperforms the network based methods with single-dimensional data and other existing approaches. Subsequent analysis of the top ranked genes suggests they may be functionally implicated in GBM, which further corroborates the superiority of the proposed method. The source code and the results of HNMD can be downloaded from the following URL: http://bioinformatics.ustc.edu.cn/hnmd/ .

The Extraction of One-Dimensional Flow Properties from Multi-Dimensional Data Sets

NASA Technical Reports Server (NTRS)

Baurle, Robert A.; Gaffney, Richard L., Jr.

2007-01-01

The engineering design and analysis of air-breathing propulsion systems relies heavily on zero- or one-dimensional properties (e.g. thrust, total pressure recovery, mixing and combustion efficiency, etc.) for figures of merit. The extraction of these parameters from experimental data sets and/or multi-dimensional computational data sets is therefore an important aspect of the design process. A variety of methods exist for extracting performance measures from multi-dimensional data sets. Some of the information contained in the multi-dimensional flow is inevitably lost when any one-dimensionalization technique is applied. Hence, the unique assumptions associated with a given approach may result in one-dimensional properties that are significantly different than those extracted using alternative approaches. The purpose of this effort is to examine some of the more popular methods used for the extraction of performance measures from multi-dimensional data sets, reveal the strengths and weaknesses of each approach, and highlight various numerical issues that result when mapping data from a multi-dimensional space to a space of one dimension.

The Art of Extracting One-Dimensional Flow Properties from Multi-Dimensional Data Sets

NASA Technical Reports Server (NTRS)

Baurle, R. A.; Gaffney, R. L.

2007-01-01

The engineering design and analysis of air-breathing propulsion systems relies heavily on zero- or one-dimensional properties (e:g: thrust, total pressure recovery, mixing and combustion efficiency, etc.) for figures of merit. The extraction of these parameters from experimental data sets and/or multi-dimensional computational data sets is therefore an important aspect of the design process. A variety of methods exist for extracting performance measures from multi-dimensional data sets. Some of the information contained in the multi-dimensional flow is inevitably lost when any one-dimensionalization technique is applied. Hence, the unique assumptions associated with a given approach may result in one-dimensional properties that are significantly different than those extracted using alternative approaches. The purpose of this effort is to examine some of the more popular methods used for the extraction of performance measures from multi-dimensional data sets, reveal the strengths and weaknesses of each approach, and highlight various numerical issues that result when mapping data from a multi-dimensional space to a space of one dimension.

Multidimensional scaling analysis of financial time series based on modified cross-sample entropy methods

NASA Astrophysics Data System (ADS)

He, Jiayi; Shang, Pengjian; Xiong, Hui

2018-06-01

Stocks, as the concrete manifestation of financial time series with plenty of potential information, are often used in the study of financial time series. In this paper, we utilize the stock data to recognize their patterns through out the dissimilarity matrix based on modified cross-sample entropy, then three-dimensional perceptual maps of the results are provided through multidimensional scaling method. Two modified multidimensional scaling methods are proposed in this paper, that is, multidimensional scaling based on Kronecker-delta cross-sample entropy (MDS-KCSE) and multidimensional scaling based on permutation cross-sample entropy (MDS-PCSE). These two methods use Kronecker-delta based cross-sample entropy and permutation based cross-sample entropy to replace the distance or dissimilarity measurement in classical multidimensional scaling (MDS). Multidimensional scaling based on Chebyshev distance (MDSC) is employed to provide a reference for comparisons. Our analysis reveals a clear clustering both in synthetic data and 18 indices from diverse stock markets. It implies that time series generated by the same model are easier to have similar irregularity than others, and the difference in the stock index, which is caused by the country or region and the different financial policies, can reflect the irregularity in the data. In the synthetic data experiments, not only the time series generated by different models can be distinguished, the one generated under different parameters of the same model can also be detected. In the financial data experiment, the stock indices are clearly divided into five groups. Through analysis, we find that they correspond to five regions, respectively, that is, Europe, North America, South America, Asian-Pacific (with the exception of mainland China), mainland China and Russia. The results also demonstrate that MDS-KCSE and MDS-PCSE provide more effective divisions in experiments than MDSC.

How Turbulence Enables Core-collapse Supernova Explosions

NASA Astrophysics Data System (ADS)

Mabanta, Quintin A.; Murphy, Jeremiah W.

2018-03-01

An important result in core-collapse supernova (CCSN) theory is that spherically symmetric, one-dimensional simulations routinely fail to explode, yet multidimensional simulations often explode. Numerical investigations suggest that turbulence eases the condition for explosion, but how it does it is not fully understood. We develop a turbulence model for neutrino-driven convection, and show that this turbulence model reduces the condition for explosions by about 30%, in concordance with multidimensional simulations. In addition, we identify which turbulent terms enable explosions. Contrary to prior suggestions, turbulent ram pressure is not the dominant factor in reducing the condition for explosion. Instead, there are many contributing factors, with ram pressure being only one of them, but the dominant factor is turbulent dissipation (TD). Primarily, TD provides extra heating, adding significant thermal pressure and reducing the condition for explosion. The source of this TD power is turbulent kinetic energy, which ultimately derives its energy from the higher potential of an unstable convective profile. Investigating a turbulence model in conjunction with an explosion condition enables insight that is difficult to glean from merely analyzing complex multidimensional simulations. An explosion condition presents a clear diagnostic to explain why stars explode, and the turbulence model allows us to explore how turbulence enables explosion. Although we find that TD is a significant contributor to successful supernova explosions, it is important to note that this work is to some extent qualitative. Therefore, we suggest ways to further verify and validate our predictions with multidimensional simulations.

A practical nonlocal model for heat transport in magnetized laser plasmas

NASA Astrophysics Data System (ADS)

Nicolaï, Ph. D.; Feugeas, J.-L. A.; Schurtz, G. P.

2006-03-01

A model of nonlocal transport for multidimensional radiation magnetohydrodynamics codes is presented. In laser produced plasmas, it is now believed that the heat transport can be strongly modified by the nonlocal nature of the electron conduction. Other mechanisms, such as self-generated magnetic fields, may also affect the heat transport. The model described in this work, based on simplified Fokker-Planck equations aims at extending the model of G. Schurtz, Ph. Nicolaï, and M. Busquet [Phys. Plasmas 7, 4238 (2000)] to magnetized plasmas. A complete system of nonlocal equations is derived from kinetic equations with self-consistent electric and magnetic fields. These equations are analyzed and simplified in order to be implemented into large laser fusion codes and coupled to other relevant physics. The model is applied to two laser configurations that demonstrate the main features of the model and point out the nonlocal Righi-Leduc effect in a multidimensional case.

High Order Finite Difference Methods, Multidimensional Linear Problems and Curvilinear Coordinates

NASA Technical Reports Server (NTRS)

Nordstrom, Jan; Carpenter, Mark H.

1999-01-01

Boundary and interface conditions are derived for high order finite difference methods applied to multidimensional linear problems in curvilinear coordinates. The boundary and interface conditions lead to conservative schemes and strict and strong stability provided that certain metric conditions are met.

Progress in multi-dimensional upwind differencing

NASA Technical Reports Server (NTRS)

Vanleer, Bram

1992-01-01

Multi-dimensional upwind-differencing schemes for the Euler equations are reviewed. On the basis of the first-order upwind scheme for a one-dimensional convection equation, the two approaches to upwind differencing are discussed: the fluctuation approach and the finite-volume approach. The usual extension of the finite-volume method to the multi-dimensional Euler equations is not entirely satisfactory, because the direction of wave propagation is always assumed to be normal to the cell faces. This leads to smearing of shock and shear waves when these are not grid-aligned. Multi-directional methods, in which upwind-biased fluxes are computed in a frame aligned with a dominant wave, overcome this problem, but at the expense of robustness. The same is true for the schemes incorporating a multi-dimensional wave model not based on multi-dimensional data but on an 'educated guess' of what they could be. The fluctuation approach offers the best possibilities for the development of genuinely multi-dimensional upwind schemes. Three building blocks are needed for such schemes: a wave model, a way to achieve conservation, and a compact convection scheme. Recent advances in each of these components are discussed; putting them all together is the present focus of a worldwide research effort. Some numerical results are presented, illustrating the potential of the new multi-dimensional schemes.

Reproducible, high-throughput synthesis of colloidal nanocrystals for optimization in multidimensional parameter space.

PubMed

Chan, Emory M; Xu, Chenxu; Mao, Alvin W; Han, Gang; Owen, Jonathan S; Cohen, Bruce E; Milliron, Delia J

2010-05-12

While colloidal nanocrystals hold tremendous potential for both enhancing fundamental understanding of materials scaling and enabling advanced technologies, progress in both realms can be inhibited by the limited reproducibility of traditional synthetic methods and by the difficulty of optimizing syntheses over a large number of synthetic parameters. Here, we describe an automated platform for the reproducible synthesis of colloidal nanocrystals and for the high-throughput optimization of physical properties relevant to emerging applications of nanomaterials. This robotic platform enables precise control over reaction conditions while performing workflows analogous to those of traditional flask syntheses. We demonstrate control over the size, size distribution, kinetics, and concentration of reactions by synthesizing CdSe nanocrystals with 0.2% coefficient of variation in the mean diameters across an array of batch reactors and over multiple runs. Leveraging this precise control along with high-throughput optical and diffraction characterization, we effectively map multidimensional parameter space to tune the size and polydispersity of CdSe nanocrystals, to maximize the photoluminescence efficiency of CdTe nanocrystals, and to control the crystal phase and maximize the upconverted luminescence of lanthanide-doped NaYF(4) nanocrystals. On the basis of these demonstrative examples, we conclude that this automated synthesis approach will be of great utility for the development of diverse colloidal nanomaterials for electronic assemblies, luminescent biological labels, electroluminescent devices, and other emerging applications.

An efficient numerical method for solving the Boltzmann equation in multidimensions

NASA Astrophysics Data System (ADS)

Dimarco, Giacomo; Loubère, Raphaël; Narski, Jacek; Rey, Thomas

2018-01-01

In this paper we deal with the extension of the Fast Kinetic Scheme (FKS) (Dimarco and Loubère, 2013 [26]) originally constructed for solving the BGK equation, to the more challenging case of the Boltzmann equation. The scheme combines a robust and fast method for treating the transport part based on an innovative Lagrangian technique supplemented with conservative fast spectral schemes to treat the collisional operator by means of an operator splitting approach. This approach along with several implementation features related to the parallelization of the algorithm permits to construct an efficient simulation tool which is numerically tested against exact and reference solutions on classical problems arising in rarefied gas dynamic. We present results up to the 3 D × 3 D case for unsteady flows for the Variable Hard Sphere model which may serve as benchmark for future comparisons between different numerical methods for solving the multidimensional Boltzmann equation. For this reason, we also provide for each problem studied details on the computational cost and memory consumption as well as comparisons with the BGK model or the limit model of compressible Euler equations.

Measuring patient satisfaction with exercise therapy for knee osteoarthritis: evaluating the utility of the physiotherapy outpatient survey.

PubMed

French, H P; Keogan, F; Gilsenan, C; Waldron, L; O'Connell, P

2010-06-01

To assess patient satisfaction with exercise for knee osteoarthritis (OA). A convenience sample of 27 patients recruited to a randomized controlled trial (RCT) comparing open kinetic chain and closed kinetic chain exercises for knee OA were reassessed at nine months post-randomization. Clinical outcomes included self-report and physical performance measures of function and pain severity. Patients also completed the Physiotherapy Outpatient Survey (POPS), which is a multi-dimensional measure of patient satisfaction with physiotherapy. There was no significant difference in satisfaction between the two intervention groups. Overall mean satisfaction for the entire cohort was 4.07 of a maximum score of 5 (standard deviation (SD) = 0.52). Lower levels of satisfaction with outcome (mean = 3.56, SD = 0.8) were reported compared with other domains of expectations, communication, organization and the therapist (mean = 3.79-4.49; SDs = 0.42-0.92). Both intervention groups improved from baseline on clinical outcomes of pain, self-report function and walking distance, with no significant differences between the two groups. High levels of satisfaction were reported in this subsample of knee OA patients participating in an RCT evaluating the effects of different exercise approaches for knee OA. Satisfaction varied depending on the satisfaction domain, with lower satisfaction with outcome compared with other aspects of care. The POPS questionnaire can be used to measure the multi-dimensional aspects of satisfaction with physiotherapy.

High-level direct-dynamics variational transition state theory calculations including multidimensional tunneling of the thermal rate constants, branching ratios, and kinetic isotope effects of the hydrogen abstraction reactions from methanol by atomic hydrogen.

PubMed

Meana-Pañeda, Rubén; Truhlar, Donald G; Fernández-Ramos, Antonio

2011-03-07

We report a detailed theoretical study of the hydrogen abstraction reaction from methanol by atomic hydrogen. The study includes the analysis of thermal rate constants, branching ratios, and kinetic isotope effects. Specifically, we have performed high-level computations at the MC3BB level together with direct dynamics calculations by canonical variational transition state theory (CVT) with the microcanonically optimized multidimensional tunneling (μOMT) transmission coefficient (CVT/μOMT) to study both the CH(3)OH+H→CH(2)OH+H(2) (R1) reaction and the CH(3)OH+H→CH(3)O+H(2) (R2) reaction. The CVT/μOMT calculations show that reaction R1 dominates in the whole range 298≤T (K)≤2500 and that anharmonic effects on the torsional mode about the C-O bond are important, mainly at high temperatures. The activation energy for the total reaction sum of R1 and R2 reactions changes substantially with temperature and, therefore, the use of straight-line Arrhenius plots is not valid. We recommend the use of new expressions for the total R1 + R2 reaction and for the R1 and R2 individual reactions. © 2011 American Institute of Physics.

Label-free assay based on immobilized capillary enzyme reactor of Leishmania infantum nucleoside triphosphate diphosphohydrolase (LicNTPDase-2-ICER-LC/UV).

PubMed

Magalhães, Luana; de Oliveira, Arthur Henrique Cavalcante; de Souza Vasconcellos, Raphael; Mariotini-Moura, Christiane; de Cássia Firmino, Rafaela; Fietto, Juliana Lopes Rangel; Cardoso, Carmen Lúcia

2016-01-01

Nucleoside triphosphate diphosphohydrolase (NTPDase) is an enzyme belonging to the apyrase family that participates in the hydrolysis of the nucleosides di- and triphosphate to the corresponding nucleoside monophosphate. This enzyme underlies the virulence of parasites such as Leishmania. Recently, an NTPDase from Leishmania infantum (LicNTPDase-2) was cloned and expressed and has been considered as a new drug target for the treatment of leishmaniasis. With the intent of developing label-free online screening methodologies, LicNTPDase-2 was covalently immobilized onto a fused silica capillary tube in the present study to create an immobilized capillary enzyme reactor (ICER) based on LicNTPDase-2 (LicNTPDase-2-ICER). To perform the activity assays, a multidimensional chromatographic method was developed employing the LicNTPDase-2-ICER in the first dimension, and an analytical Ascentis C8 column was used in the second dimension to provide analytical separation of the substrates and products. The validated LicNTPDase-2-ICER method provided the following kinetic parameters of the immobilized enzyme: KM of 2.2 and 1.8mmolL(-1) for the ADP and ATP substrates, respectively. Suramin (1mmolL(-1)) was also shown to inhibit 32.9% of the enzymatic activity. The developed method is applicable to kinetic studies and enables the recognition of the ligands. Furthermore, a comparison of the values of LicNTPDase-2-ICER with those obtained with an LC method using free enzyme in solution showed that LicNTPDase-2-ICER-LC/UV was an accurate and reproducible method that enabled automated measurements for the rapid screening of ligands. Copyright © 2015 Elsevier B.V. All rights reserved.

Material discovery by combining stochastic surface walking global optimization with a neural network.

PubMed

Huang, Si-Da; Shang, Cheng; Zhang, Xiao-Jie; Liu, Zhi-Pan

2017-09-01

While the underlying potential energy surface (PES) determines the structure and other properties of a material, it has been frustrating to predict new materials from theory even with the advent of supercomputing facilities. The accuracy of the PES and the efficiency of PES sampling are two major bottlenecks, not least because of the great complexity of the material PES. This work introduces a "Global-to-Global" approach for material discovery by combining for the first time a global optimization method with neural network (NN) techniques. The novel global optimization method, named the stochastic surface walking (SSW) method, is carried out massively in parallel for generating a global training data set, the fitting of which by the atom-centered NN produces a multi-dimensional global PES; the subsequent SSW exploration of large systems with the analytical NN PES can provide key information on the thermodynamics and kinetics stability of unknown phases identified from global PESs. We describe in detail the current implementation of the SSW-NN method with particular focuses on the size of the global data set and the simultaneous energy/force/stress NN training procedure. An important functional material, TiO 2 , is utilized as an example to demonstrate the automated global data set generation, the improved NN training procedure and the application in material discovery. Two new TiO 2 porous crystal structures are identified, which have similar thermodynamics stability to the common TiO 2 rutile phase and the kinetics stability for one of them is further proved from SSW pathway sampling. As a general tool for material simulation, the SSW-NN method provides an efficient and predictive platform for large-scale computational material screening.

An asymptotic preserving multidimensional ALE method for a system of two compressible flows coupled with friction

NASA Astrophysics Data System (ADS)

Del Pino, S.; Labourasse, E.; Morel, G.

2018-06-01

We present a multidimensional asymptotic preserving scheme for the approximation of a mixture of compressible flows. Fluids are modelled by two Euler systems of equations coupled with a friction term. The asymptotic preserving property is mandatory for this kind of model, to derive a scheme that behaves well in all regimes (i.e. whatever the friction parameter value is). The method we propose is defined in ALE coordinates, using a Lagrange plus remap approach. This imposes a multidimensional definition and analysis of the scheme.

Patent data mining method and apparatus

DOEpatents

Boyack, Kevin W.; Grafe, V. Gerald; Johnson, David K.; Wylie, Brian N.

2002-01-01

A method of data mining represents related patents in a multidimensional space. Distance between patents in the multidimensional space corresponds to the extent of relationship between the patents. The relationship between pairings of patents can be expressed based on weighted combinations of several predicates. The user can select portions of the space to perceive. The user also can interact with and control the communication of the space, focusing attention on aspects of the space of most interest. The multidimensional spatial representation allows more ready comprehension of the structure of the relationships among the patents.

Using the Pearson Distribution for Synthesis of the Suboptimal Algorithms for Filtering Multi-Dimensional Markov Processes

NASA Astrophysics Data System (ADS)

Mit'kin, A. S.; Pogorelov, V. A.; Chub, E. G.

2015-08-01

We consider the method of constructing the suboptimal filter on the basis of approximating the a posteriori probability density of the multidimensional Markov process by the Pearson distributions. The proposed method can efficiently be used for approximating asymmetric, excessive, and finite densities.

The Necessity-Concerns-Framework: A Multidimensional Theory Benefits from Multidimensional Analysis

PubMed Central

Phillips, L. Alison; Diefenbach, Michael; Kronish, Ian M.; Negron, Rennie M.; Horowitz, Carol R.

2014-01-01

Background Patients’ medication-related concerns and necessity-beliefs predict adherence. Evaluation of the potentially complex interplay of these two dimensions has been limited because of methods that reduce them to a single dimension (difference scores). Purpose We use polynomial regression to assess the multidimensional effect of stroke-event survivors’ medication-related concerns and necessity-beliefs on their adherence to stroke-prevention medication. Methods Survivors (n=600) rated their concerns, necessity-beliefs, and adherence to medication. Confirmatory and exploratory polynomial regression determined the best-fitting multidimensional model. Results As posited by the Necessity-Concerns Framework (NCF), the greatest and lowest adherence was reported by those with strong necessity-beliefs/weak concerns and strong concerns/weak necessity-beliefs, respectively. However, as could not be assessed using a difference-score model, patients with ambivalent beliefs were less adherent than those exhibiting indifference. Conclusions Polynomial regression allows for assessment of the multidimensional nature of the NCF. Clinicians/Researchers should be aware that concerns and necessity dimensions are not polar opposites. PMID:24500078

Reduced detonation kinetics and detonation structure in one- and multi-fuel gaseous mixtures

NASA Astrophysics Data System (ADS)

Fomin, P. A.; Trotsyuk, A. V.; Vasil'ev, A. A.

2017-10-01

Two-step approximate models of chemical kinetics of detonation combustion of (i) one-fuel (CH4/air) and (ii) multi-fuel gaseous mixtures (CH4/H2/air and CH4/CO/air) are developed for the first time. The models for multi-fuel mixtures are proposed for the first time. Owing to the simplicity and high accuracy, the models can be used in multi-dimensional numerical calculations of detonation waves in corresponding gaseous mixtures. The models are in consistent with the second law of thermodynamics and Le Chatelier’s principle. Constants of the models have a clear physical meaning. Advantages of the kinetic model for detonation combustion of methane has been demonstrated via numerical calculations of a two-dimensional structure of the detonation wave in a stoichiometric and fuel-rich methane-air mixtures and stoichiometric methane-oxygen mixture. The dominant size of the detonation cell, determines in calculations, is in good agreement with all known experimental data.

Evidence for tunneling in base-catalyzed isomerization of glyceraldehyde to dihydroxyacetone by hydride shift under formose conditions.

PubMed

Cheng, Liang; Doubleday, Charles; Breslow, Ronald

2015-04-07

Hydrogen atom transfer reactions between the aldose and ketose are key mechanistic features in formose chemistry by which formaldehyde is converted to higher sugars under credible prebiotic conditions. For one of these transformations, we have investigated whether hydrogen tunneling makes a significant contribution to the mechanism by examining the deuterium kinetic isotope effect associated with the hydrogen transfer during the isomerization of glyceraldehyde to the corresponding dihydroxyacetone. To do this, we developed a quantitative HPLC assay that allowed us to measure the apparent large intrinsic kinetic isotope effect. From the Arrhenius plot of the kinetic isotope effect, the ratio of the preexponential factors AH/AD was 0.28 and the difference in activation energies Ea(D) - Ea(H) was 9.1 kJ·mol(-1). All these results imply a significant quantum-mechanical tunneling component in the isomerization mechanism. This is supported by multidimensional tunneling calculations using POLYRATE with small curvature tunneling.

Multidimensional CAT Item Selection Methods for Domain Scores and Composite Scores with Item Exposure Control and Content Constraints

ERIC Educational Resources Information Center

Yao, Lihua

2014-01-01

The intent of this research was to find an item selection procedure in the multidimensional computer adaptive testing (CAT) framework that yielded higher precision for both the domain and composite abilities, had a higher usage of the item pool, and controlled the exposure rate. Five multidimensional CAT item selection procedures (minimum angle;…

Uniqueness of thermodynamic projector and kinetic basis of molecular individualism

NASA Astrophysics Data System (ADS)

Gorban, Alexander N.; Karlin, Iliya V.

2004-05-01

Three results are presented: First, we solve the problem of persistence of dissipation for reduction of kinetic models. Kinetic equations with thermodynamic Lyapunov functions are studied. Uniqueness of the thermodynamic projector is proven: There exists only one projector which transforms any vector field equipped with the given Lyapunov function into a vector field with the same Lyapunov function for a given anzatz manifold which is not tangent to the Lyapunov function levels. Second, we use the thermodynamic projector for developing the short memory approximation and coarse-graining for general nonlinear dynamic systems. We prove that in this approximation the entropy production increases. ( The theorem about entropy overproduction.) In example, we apply the thermodynamic projector to derive the equations of reduced kinetics for the Fokker-Planck equation. A new class of closures is developed, the kinetic multipeak polyhedra. Distributions of this type are expected in kinetic models with multidimensional instability as universally as the Gaussian distribution appears for stable systems. The number of possible relatively stable states of a nonequilibrium system grows as 2 m, and the number of macroscopic parameters is in order mn, where n is the dimension of configuration space, and m is the number of independent unstable directions in this space. The elaborated class of closures and equations pretends to describe the effects of “molecular individualism”. This is the third result.

An Examination of Alternative Multidimensional Scaling Techniques

ERIC Educational Resources Information Center

Papazoglou, Sofia; Mylonas, Kostas

2017-01-01

The purpose of this study is to compare alternative multidimensional scaling (MDS) methods for constraining the stimuli on the circumference of a circle and on the surface of a sphere. Specifically, the existing MDS-T method for plotting the stimuli on the circumference of a circle is applied, and its extension is proposed for constraining the…

Probes for multidimensional nanospectroscopic imaging and methods of fabrication thereof

DOEpatents

Weber-Bargioni, Alexander; Cabrini, Stefano; Bao, Wei; Melli, Mauro; Yablonovitch, Eli; Schuck, Peter J

2015-03-17

This disclosure provides systems, methods, and apparatus related to probes for multidimensional nanospectroscopic imaging. In one aspect, a method includes providing a transparent tip comprising a dielectric material. A four-sided pyramidal-shaped structure is formed at an apex of the transparent tip using a focused ion beam. Metal layers are deposited over two opposing sides of the four-sided pyramidal-shaped structure.

Markov-chain model of classified atomistic transition states for discrete kinetic Monte Carlo simulations.

PubMed

Numazawa, Satoshi; Smith, Roger

2011-10-01

Classical harmonic transition state theory is considered and applied in discrete lattice cells with hierarchical transition levels. The scheme is then used to determine transitions that can be applied in a lattice-based kinetic Monte Carlo (KMC) atomistic simulation model. The model results in an effective reduction of KMC simulation steps by utilizing a classification scheme of transition levels for thermally activated atomistic diffusion processes. Thermally activated atomistic movements are considered as local transition events constrained in potential energy wells over certain local time periods. These processes are represented by Markov chains of multidimensional Boolean valued functions in three-dimensional lattice space. The events inhibited by the barriers under a certain level are regarded as thermal fluctuations of the canonical ensemble and accepted freely. Consequently, the fluctuating system evolution process is implemented as a Markov chain of equivalence class objects. It is shown that the process can be characterized by the acceptance of metastable local transitions. The method is applied to a problem of Au and Ag cluster growth on a rippled surface. The simulation predicts the existence of a morphology-dependent transition time limit from a local metastable to stable state for subsequent cluster growth by accretion. Excellent agreement with observed experimental results is obtained.

A one-dimensional free energy surface does not account for two-probe folding kinetics of protein alpha(3)D.

PubMed

Liu, Feng; Dumont, Charles; Zhu, Yongjin; DeGrado, William F; Gai, Feng; Gruebele, Martin

2009-02-14

We present fluorescence-detected measurements of the temperature-jump relaxation kinetics of the designed three-helix bundle protein alpha(3)D taken under solvent conditions identical to previous infrared-detected kinetics. The fluorescence-detected rate is similar to the IR-detected rate only at the lowest temperature where we could measure it (326 K). The fluorescence-detected rate decreases by a factor of 3 over the 326-344 K temperature range, whereas the IR-detected rate remains nearly constant over the same range. To investigate this probe dependence, we tested an extensive set of physically reasonable one-dimensional (1D) free energy surfaces by Langevin dynamics simulation. The simulations included coordinate- and temperature-dependent roughness, diffusion coefficients, and IR/fluorescence spectroscopic signatures. None of these can reproduce the IR and fluorescence data simultaneously, forcing us to the conclusion that a 1D free energy surface cannot accurately describe the folding of alpha(3)D. This supports the hypothesis that alpha(3)D has a multidimensional free energy surface conducive to downhill folding at 326 K, and that it is already an incipient downhill folder with probe-dependent kinetics near its melting point.

Fundamental properties of Fanaroff-Riley type II radio galaxies investigated via Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Kapińska, A. D.; Uttley, P.; Kaiser, C. R.

2012-08-01

Radio galaxies and quasars are among the largest and most powerful single objects known and are believed to have had a significant impact on the evolving Universe and its large-scale structure. We explore the intrinsic and extrinsic properties of the population of Fanaroff-Riley type II (FR II) objects, i.e. their kinetic luminosities, lifetimes and the central densities of their environments. In particular, the radio and kinetic luminosity functions of these powerful radio sources are investigated using the complete, flux-limited radio catalogues of the Third Cambridge Revised Revised Catalogue (3CRR) and Best et al. We construct multidimensional Monte Carlo simulations using semi-analytical models of FR II source time evolution to create artificial samples of radio galaxies. Unlike previous studies, we compare radio luminosity functions found with both the observed and simulated data to explore the best-fitting fundamental source parameters. The new Monte Carlo method we present here allows us to (i) set better limits on the predicted fundamental parameters of which confidence intervals estimated over broad ranges are presented and (ii) generate the most plausible underlying parent populations of these radio sources. Moreover, as has not been done before, we allow the source physical properties (kinetic luminosities, lifetimes and central densities) to co-evolve with redshift, and we find that all the investigated parameters most likely undergo cosmological evolution. Strikingly, we find that the break in the kinetic luminosity function must undergo redshift evolution of at least (1 + z)3. The fundamental parameters are strongly degenerate, and independent constraints are necessary to draw more precise conclusions. We use the estimated kinetic luminosity functions to set constraints on the duty cycles of these powerful radio sources. A comparison of the duty cycles of powerful FR IIs with those determined from radiative luminosities of active galactic nuclei of comparable black hole mass suggests a transition in behaviour from high to low redshifts, corresponding to either a drop in the typical black hole mass of powerful FR IIs at low redshifts, or a transition to a kinetically dominated, radiatively inefficient FR II population.

Effects of Multidimensional Family Therapy (MDFT) on Nonopioid Drug Abuse: A Systematic Review and Meta-Analysis

ERIC Educational Resources Information Center

Filges, Trine; Andersen, Ditte; Jørgensen, Anne-Marie Klint

2018-01-01

Purpose: This review evaluates the evidence of the effects of multidimensional family therapy (MDFT) on drug use reduction in young people for the treatment of nonopioid drug use. Method: We followed Campbell Collaboration guidelines to conduct a systematic review of randomized and nonrandomized trials. Meta-analytic methods were used to…

Vacuum polarization in the field of a multidimensional global monopole

NASA Astrophysics Data System (ADS)

Grats, Yu. V.; Spirin, P. A.

2016-11-01

An approximate expression for the Euclidean Green function of a massless scalar field in the spacetime of a multidimensional global monopole has been derived. Expressions for the vacuum expectation values <ϕ2>ren and < T 00>ren have been derived by the dimensional regularization method. Comparison with the results obtained by alternative regularization methods is made.

The Versatility of SpAM: A Fast, Efficient, Spatial Method of Data Collection for Multidimensional Scaling

ERIC Educational Resources Information Center

Hout, Michael C.; Goldinger, Stephen D.; Ferguson, Ryan W.

2013-01-01

Although traditional methods to collect similarity data (for multidimensional scaling [MDS]) are robust, they share a key shortcoming. Specifically, the possible pairwise comparisons in any set of objects grow rapidly as a function of set size. This leads to lengthy experimental protocols, or procedures that involve scaling stimulus subsets. We…

Invited Article: Single-shot THz detection techniques optimized for multidimensional THz spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teo, Stephanie M.; Ofori-Okai, Benjamin K.; Werley, Christopher A.

Multidimensional spectroscopy at visible and infrared frequencies has opened a window into the transfer of energy and quantum coherences at ultrafast time scales. For these measurements to be performed in a manageable amount of time, one spectral axis is typically recorded in a single laser shot. An analogous rapid-scanning capability for THz measurements will unlock the multidimensional toolkit in this frequency range. Here, we first review the merits of existing single-shot THz schemes and discuss their potential in multidimensional THz spectroscopy. We then introduce improved experimental designs and noise suppression techniques for the two most promising methods: frequency-to-time encoding withmore » linear spectral interferometry and angle-to-time encoding with dual echelons. Both methods, each using electro-optic detection in the linear regime, were able to reproduce the THz temporal waveform acquired with a traditional scanning delay line. Although spectral interferometry had mediocre performance in terms of signal-to-noise, the dual echelon method was easily implemented and achieved the same level of signal-to-noise as the scanning delay line in only 4.5% of the laser pulses otherwise required (or 22 times faster). This reduction in acquisition time will compress day-long scans to hours and hence provides a practical technique for multidimensional THz measurements.« less

Invited Article: Single-shot THz detection techniques optimized for multidimensional THz spectroscopy.

PubMed

Teo, Stephanie M; Ofori-Okai, Benjamin K; Werley, Christopher A; Nelson, Keith A

2015-05-01

Multidimensional spectroscopy at visible and infrared frequencies has opened a window into the transfer of energy and quantum coherences at ultrafast time scales. For these measurements to be performed in a manageable amount of time, one spectral axis is typically recorded in a single laser shot. An analogous rapid-scanning capability for THz measurements will unlock the multidimensional toolkit in this frequency range. Here, we first review the merits of existing single-shot THz schemes and discuss their potential in multidimensional THz spectroscopy. We then introduce improved experimental designs and noise suppression techniques for the two most promising methods: frequency-to-time encoding with linear spectral interferometry and angle-to-time encoding with dual echelons. Both methods, each using electro-optic detection in the linear regime, were able to reproduce the THz temporal waveform acquired with a traditional scanning delay line. Although spectral interferometry had mediocre performance in terms of signal-to-noise, the dual echelon method was easily implemented and achieved the same level of signal-to-noise as the scanning delay line in only 4.5% of the laser pulses otherwise required (or 22 times faster). This reduction in acquisition time will compress day-long scans to hours and hence provides a practical technique for multidimensional THz measurements.

A two-column formalism for time-dependent modelling of stellar convection. I. Description of the method

NASA Astrophysics Data System (ADS)

Stökl, A.

2008-11-01

Context: In spite of all the advances in multi-dimensional hydrodynamics, investigations of stellar evolution and stellar pulsations still depend on one-dimensional computations. This paper devises an alternative to the mixing-length theory or turbulence models usually adopted in modelling convective transport in such studies. Aims: The present work attempts to develop a time-dependent description of convection, which reflects the essential physics of convection and that is only moderately dependent on numerical parameters and far less time consuming than existing multi-dimensional hydrodynamics computations. Methods: Assuming that the most extensive convective patterns generate the majority of convective transport, the convective velocity field is described using two parallel, radial columns to represent up- and downstream flows. Horizontal exchange, in the form of fluid flow and radiation, over their connecting interface couples the two columns and allows a simple circulating motion. The main parameters of this convective description have straightforward geometrical meanings, namely the diameter of the columns (corresponding to the size of the convective cells) and the ratio of the cross-section between up- and downdrafts. For this geometrical setup, the time-dependent solution of the equations of radiation hydrodynamics is computed from an implicit scheme that has the advantage of being unaffected by the Courant-Friedrichs-Lewy time-step limit. This implementation is part of the TAPIR-Code (short for The adaptive, implicit RHD-Code). Results: To demonstrate the approach, results for convection zones in Cepheids are presented. The convective energy transport and convective velocities agree with expectations for Cepheids and the scheme reproduces both the kinetic energy flux and convective overshoot. A study of the parameter influence shows that the type of solution derived for these stars is in fact fairly robust with respect to the constitutive numerical parameters.

A high order cell-centered semi-Lagrangian scheme for multi-dimensional kinetic simulations of neutral gas flows

NASA Astrophysics Data System (ADS)

Güçlü, Y.; Hitchon, W. N. G.

2012-04-01

The term 'Convected Scheme' (CS) refers to a family of algorithms, most usually applied to the solution of Boltzmann's equation, which uses a method of characteristics in an integral form to project an initial cell forward to a group of final cells. As such the CS is a 'forward-trajectory' semi-Lagrangian scheme. For multi-dimensional simulations of neutral gas flows, the cell-centered version of this semi-Lagrangian (CCSL) scheme has advantages over other options due to its implementation simplicity, low memory requirements, and easier treatment of boundary conditions. The main drawback of the CCSL-CS to date has been its high numerical diffusion in physical space, because of the 2nd order remapping that takes place at the end of each time step. By means of a modified equation analysis, it is shown that a high order estimate of the remapping error can be obtained a priori, and a small correction to the final position of the cells can be applied upon remapping, in order to achieve full compensation of this error. The resulting scheme is 4th order accurate in space while retaining the desirable properties of the CS: it is conservative and positivity-preserving, and the overall algorithm complexity is not appreciably increased. Two monotone (i.e. non-oscillating) versions of the fourth order CCSL-CS are also presented: one uses a common flux-limiter approach; the other uses a non-polynomial reconstruction to evaluate the derivatives of the density function. The method is illustrated in simple one- and two-dimensional examples, and a fully 3D solution of the Boltzmann equation describing expansion of a gas into vacuum through a cylindrical tube.

Increasing Accuracy of Tissue Shear Modulus Reconstruction Using Ultrasonic Strain Tensor Measurement

NASA Astrophysics Data System (ADS)

Sumi, C.

Previously, we developed three displacement vector measurement methods, i.e., the multidimensional cross-spectrum phase gradient method (MCSPGM), the multidimensional autocorrelation method (MAM), and the multidimensional Doppler method (MDM). To increase the accuracies and stabilities of lateral and elevational displacement measurements, we also developed spatially variant, displacement component-dependent regularization. In particular, the regularization of only the lateral/elevational displacements is advantageous for the lateral unmodulated case. The demonstrated measurements of the displacement vector distributions in experiments using an inhomogeneous shear modulus agar phantom confirm that displacement-component-dependent regularization enables more stable shear modulus reconstruction. In this report, we also review our developed lateral modulation methods that use Parabolic functions, Hanning windows, and Gaussian functions in the apodization function and the optimized apodization function that realizes the designed point spread function (PSF). The modulations significantly increase the accuracy of the strain tensor measurement and shear modulus reconstruction (demonstrated using an agar phantom).

Multi-dimensional mesoscale simulations of detonation initiation in energetic materials with density-based kinetics

NASA Astrophysics Data System (ADS)

Jackson, Thomas Luther; Jost, Antoine M. D.; Zhang, Ju; Sridharan, Prashanth; Amadio, Guilherme

2018-03-01

In this work we present multi-dimensional mesoscale simulations of detonation initiation in energetic materials. We solve the reactive Euler equations, with the energy equation augmented by a power deposition term. The reaction rate at the mesoscale is modelled using density-based kinetics, while the deposition term is based on simulations of void collapse at the microscale, modelled at the mesoscale as hot spots. We carry out two- and three-dimensional mesoscale simulations of random packs of HMX crystals in a binder, and show that transition between no-detonation and detonation depends on the number density of the hot spots, the packing fraction, and the post-shock pressure of an imposed shock. In particular, we show that, for a fixed post-shock pressure, there exists a critical value of the number density of hot spots, such that when the number density is below this value a detonation wave will not develop. We highlight the importance of morphology to initiation by comparing with a homogeneous counterpart, and we compare relevant length scales by examining their corresponding power spectra. We also examine the effect of packing fraction and show that at low post-shock pressures there is significant variation in the initiation times, but that this variation disappears as the post-shock pressure is increased. Finally, we compare three-dimensional simulations with the experimental data, and show that the model is capable of qualitatively reproducing the trends shown in the data.

Numerical simulation of two-dimensional flow over a heated carbon surface with coupled heterogeneous and homogeneous reactions

NASA Astrophysics Data System (ADS)

Johnson, Ryan Federick; Chelliah, Harsha Kumar

2017-01-01

For a range of flow and chemical timescales, numerical simulations of two-dimensional laminar flow over a reacting carbon surface were performed to understand further the complex coupling between heterogeneous and homogeneous reactions. An open-source computational package (OpenFOAM®) was used with previously developed lumped heterogeneous reaction models for carbon surfaces and a detailed homogeneous reaction model for CO oxidation. The influence of finite-rate chemical kinetics was explored by varying the surface temperatures from 1800 to 2600 K, while flow residence time effects were explored by varying the free-stream velocity up to 50 m/s. The reacting boundary layer structure dependence on the residence time was analysed by extracting the ratio of chemical source and species diffusion terms. The important contributions of radical species reactions on overall carbon removal rate, which is often neglected in multi-dimensional simulations, are highlighted. The results provide a framework for future development and validation of lumped heterogeneous reaction models based on multi-dimensional reacting flow configurations.

Free energy surfaces for the interaction of D-glucose with planar aromatic groups in aqueous solution

NASA Astrophysics Data System (ADS)

Wohlert, Jakob; Schnupf, Udo; Brady, John W.

2010-10-01

Multidimensional potentials of mean force for the interactions in aqueous solution of both anomers of D-glucopyranose with two planar aromatic molecules, indole and para-methyl-phenol, have been calculated using molecular dynamics simulations with umbrella sampling and were subsequently used to estimate binding free energies. Indole and para-methyl-phenol serve as models for the side chains of the amino acids tryptophan and tyrosine, respectively. In all cases, a weak affinity between the glucose molecules and the flat aromatic surfaces was found. The global minimum for these interactions was found to be for the case when the pseudoplanar face of β-D-glucopyranose is stacked against the planar surfaces of the aromatic residues. The calculated binding free energies are in good agreement with both experiment and previous simulations. The multidimensional free energy maps suggest a mechanism that could lend kinetic stability to the complexes formed by sugars bound to sugar-binding proteins.

Multidimensional kinetic simulations using dissipative closures and other reduced Vlasov methods for differing particle magnetizations

NASA Astrophysics Data System (ADS)

Newman, David L.

2006-10-01

Kinetic plasma simulations in which the phase-space distribution functions are advanced directly via the coupled Vlasov and Poisson (or Maxwell) equations---better known simply as Vlasov simulations---provide a valuable low-noise complement to the more commonly employed Particle-in-Cell (PIC) simulations. However, in more than one spatial dimension Vlasov simulations become numerically demanding due to the high dimensionality of x--v phase-space. Methods that can reduce this computational demand are therefore highly desirable. Several such methods will be presented, which treat the phase-space dynamics along a dominant dimension (e.g., parallel to a beam or current) with the full Vlasov propagator, while employing a reduced description, such as moment equations, for the evolution perpendicular to the dominant dimension. A key difference between the moment-based (and other reduced) methods considered here and standard fluid methods is that the moments are now functions of a phase-space coordinate (e.g. moments of vy in z--vz--y phase space, where z is the dominant dimension), rather than functions of spatial coordinates alone. Of course, moment-based methods require closure. For effectively unmagnetized species, new dissipative closure methods inspired by those of Hammett and Perkins [PRL, 64, 3019 (1990)] have been developed, which exactly reproduce the linear electrostatic response for a broad class of distributions with power-law tails, as are commonly measured in space plasmas. The nonlinear response, which requires more care, will also be discussed. For weakly magnetized species (i.e., φs<φs) an alternative algorithm has been developed in which the distributions are assumed to gyrate about the magnetic field with a fixed nominal perpendicular ``thermal'' velocity, thereby reducing the required phase-space dimension by one. These reduced algorithms have been incorporated into 2-D codes used to study the evolution of nonlinear structures such as double layers and electron holes in Earth's auroral zone.

The space transformation in the simulation of multidimensional random fields

USGS Publications Warehouse

Christakos, G.

1987-01-01

Space transformations are proposed as a mathematically meaningful and practically comprehensive approach to simulate multidimensional random fields. Within this context the turning bands method of simulation is reconsidered and improved in both the space and frequency domains. ?? 1987.

Multidimensional Risk Analysis: MRISK

NASA Technical Reports Server (NTRS)

McCollum, Raymond; Brown, Douglas; O'Shea, Sarah Beth; Reith, William; Rabulan, Jennifer; Melrose, Graeme

2015-01-01

Multidimensional Risk (MRISK) calculates the combined multidimensional score using Mahalanobis distance. MRISK accounts for covariance between consequence dimensions, which de-conflicts the interdependencies of consequence dimensions, providing a clearer depiction of risks. Additionally, in the event the dimensions are not correlated, Mahalanobis distance reduces to Euclidean distance normalized by the variance and, therefore, represents the most flexible and optimal method to combine dimensions. MRISK is currently being used in NASA's Environmentally Responsible Aviation (ERA) project o assess risk and prioritize scarce resources.

Electron plasma wave filamentation in the kinetic regime

NASA Astrophysics Data System (ADS)

Lushnikov, Pavel; Rose, Harvey; Silantyev, Denis

2016-10-01

We consider nonlinear electron plasma wave (EPW) dynamics in the kinetic wavenumber regime, 0.25 < kλD < 0.45 , which is typical for current high temperature laser-plasma interaction experiments, where k is the EPW wavenumber and λD is the electron Debye length. In this kinetic regime, EPW frequency reduction due to electron trapping may dominate the ponderomotive frequency shift. Previous 3D PIC simulations showed that the trapped electron EPW filamentation instability can saturate stimulated Raman backscatter by reducing the EPWs coherence but multidimensional Vlasov simulations [1] are needed to address that saturation in details. We performed nonlinear, non-equilibrium 2D Vlasov simulations to study the EPW filamentation. The initial conditions are created either by external forcing or by constructing the appropriate 1D travelling Bernstein-Greene-Kruskal (BGK) mode. Transverse perturbations of any of these initial conditions grow with time eventually producing strongly nonlinear filamentation followed by plasma turbulence. We compared these simulations with the theoretical results on growth rates of the transverse instability BGK mode showing the satisfactory agreement. Supported by the New Mexico Consortium and NSF DMS-1412140.

Using a multidimensional unfolding approach to assess multiple sclerosis patient preferences for disease-modifying therapy: a pilot study

PubMed Central

Sempere, Angel Perez; Vera-Lopez, Vanesa; Gimenez-Martinez, Juana; Ruiz-Beato, Elena; Cuervo, Jesús; Maurino, Jorge

2017-01-01

Purpose Multidimensional unfolding is a multivariate method to assess preferences using a small sample size, a geometric model locating individuals and alternatives as points in a joint space. The objective was to evaluate relapsing–remitting multiple sclerosis (RRMS) patient preferences toward key disease-modifying therapy (DMT) attributes using multidimensional unfolding. Patients and methods A cross-sectional pilot study in RRMS patients was conducted. Drug attributes included relapse prevention, disease progression prevention, side-effect risk and route and schedule of administration. Assessment of preferences was performed through a five-card game. Patients were asked to value attributes from 1 (most preferred) to 5 (least preferred). Results A total of 37 patients were included; the mean age was 38.6 years, and 78.4% were female. Disease progression prevention was the most important factor (51.4%), followed by relapse prevention (40.5%). The frequency of administration had the lowest preference rating for 56.8% of patients. Finally, 19.6% valued the side-effect risk attribute as having low/very low importance. Conclusion Patients’ perspective for DMT attributes may provide valuable information to facilitate shared decision-making. Efficacy attributes were the most important drug characteristics for RRMS patients. Multidimensional unfolding seems to be a feasible approach to assess preferences in multiple sclerosis patients. Further elicitation studies using multidimensional unfolding with other stated choice methods are necessary to confirm these findings. PMID:28615928

Frequency-Comb Based Double-Quantum Two-Dimensional Spectrum Identifies Collective Hyperfine Resonances in Atomic Vapor Induced by Dipole-Dipole Interactions

NASA Astrophysics Data System (ADS)

Lomsadze, Bachana; Cundiff, Steven T.

2018-06-01

Frequency-comb based multidimensional coherent spectroscopy is a novel optical method that enables high-resolution measurement in a short acquisition time. The method's resolution makes multidimensional coherent spectroscopy relevant for atomic systems that have narrow resonances. We use double-quantum multidimensional coherent spectroscopy to reveal collective hyperfine resonances in rubidium vapor at 100 °C induced by dipole-dipole interactions. We observe tilted and elongated line shapes in the double-quantum 2D spectra, which have never been reported for Doppler-broadened systems. The elongated line shapes suggest that the signal is predominately from the interacting atoms that have a near zero relative velocity.

Multidimensional radiative transfer with multilevel atoms. II. The non-linear multigrid method.

NASA Astrophysics Data System (ADS)

Fabiani Bendicho, P.; Trujillo Bueno, J.; Auer, L.

1997-08-01

A new iterative method for solving non-LTE multilevel radiative transfer (RT) problems in 1D, 2D or 3D geometries is presented. The scheme obtains the self-consistent solution of the kinetic and RT equations at the cost of only a few (<10) formal solutions of the RT equation. It combines, for the first time, non-linear multigrid iteration (Brandt, 1977, Math. Comp. 31, 333; Hackbush, 1985, Multi-Grid Methods and Applications, springer-Verlag, Berlin), an efficient multilevel RT scheme based on Gauss-Seidel iterations (cf. Trujillo Bueno & Fabiani Bendicho, 1995ApJ...455..646T), and accurate short-characteristics formal solution techniques. By combining a valid stopping criterion with a nested-grid strategy a converged solution with the desired true error is automatically guaranteed. Contrary to the current operator splitting methods the very high convergence speed of the new RT method does not deteriorate when the grid spatial resolution is increased. With this non-linear multigrid method non-LTE problems discretized on N grid points are solved in O(N) operations. The nested multigrid RT method presented here is, thus, particularly attractive in complicated multilevel transfer problems where small grid-sizes are required. The properties of the method are analyzed both analytically and with illustrative multilevel calculations for Ca II in 1D and 2D schematic model atmospheres.

Membership determination of open clusters based on a spectral clustering method

NASA Astrophysics Data System (ADS)

Gao, Xin-Hua

2018-06-01

We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.

Optimal multi-dimensional poverty lines: The state of poverty in Iraq

NASA Astrophysics Data System (ADS)

Ameen, Jamal R. M.

2017-09-01

Poverty estimation based on calories intake is unrealistic. The established concept of multidimensional poverty has methodological weaknesses in the treatment of different dimensions and there is disagreement in methods of combining them into a single poverty line. This paper introduces a methodology to estimate optimal multidimensional poverty lines and uses the Iraqi household socio-economic survey data of 2012 to demonstrate the idea. The optimal poverty line for Iraq is found to be 170.5 Thousand Iraqi Dinars (TID).

Kinetics study of the CN + CH4 hydrogen abstraction reaction based on a new ab initio analytical full-dimensional potential energy surface.

PubMed

Espinosa-Garcia, Joaquin; Rangel, Cipriano; Suleimanov, Yury V

2017-07-26

We have developed an analytical full-dimensional potential energy surface, named PES-2017, for the gas-phase hydrogen abstraction reaction between the cyano radical and methane. This surface is fitted using high-level ab initio information as input. Using the PES-2017 surface, a kinetics study was performed via two theoretical approaches: variational transition-state theory with multidimensional tunnelling (VTST-MT) and ring polymer molecular dynamics (RPMD). The results are compared with the experimental data. In the whole temperature range analysed, 300-1500 K, both theories agree within a factor of <2, reproducing the experimental behaviour taking into account the experimental uncertainties. At high temperatures, where the recrossing effects dominate and the RPMD theory is exact, both theories differ by a factor of about 20%; while at low temperatures this difference is larger, 45%. Note that in this temperature regime, the tunnelling effect is negligible. The CN + CH 4 /CD 4 kinetic isotope effects are important, reproducing the scarce experimental evidence. The good agreement with the ab initio information used in the fitting process (self-consistency test) and with the kinetic behaviour in a wide temperature range gives confidence and strength to the new surface.

Connecting the dots across time: reconstruction of single-cell signalling trajectories using time-stamped data

NASA Astrophysics Data System (ADS)

Mukherjee, Sayak; Stewart, David; Stewart, William; Lanier, Lewis L.; Das, Jayajit

2017-08-01

Single-cell responses are shaped by the geometry of signalling kinetic trajectories carved in a multidimensional space spanned by signalling protein abundances. It is, however, challenging to assay a large number (more than 3) of signalling species in live-cell imaging, which makes it difficult to probe single-cell signalling kinetic trajectories in large dimensions. Flow and mass cytometry techniques can measure a large number (4 to more than 40) of signalling species but are unable to track single cells. Thus, cytometry experiments provide detailed time-stamped snapshots of single-cell signalling kinetics. Is it possible to use the time-stamped cytometry data to reconstruct single-cell signalling trajectories? Borrowing concepts of conserved and slow variables from non-equilibrium statistical physics we develop an approach to reconstruct signalling trajectories using snapshot data by creating new variables that remain invariant or vary slowly during the signalling kinetics. We apply this approach to reconstruct trajectories using snapshot data obtained from in silico simulations, live-cell imaging measurements, and, synthetic flow cytometry datasets. The application of invariants and slow variables to reconstruct trajectories provides a radically different way to track objects using snapshot data. The approach is likely to have implications for solving matching problems in a wide range of disciplines.

Tensor-Train Split-Operator Fourier Transform (TT-SOFT) Method: Multidimensional Nonadiabatic Quantum Dynamics.

PubMed

Greene, Samuel M; Batista, Victor S

2017-09-12

We introduce the "tensor-train split-operator Fourier transform" (TT-SOFT) method for simulations of multidimensional nonadiabatic quantum dynamics. TT-SOFT is essentially the grid-based SOFT method implemented in dynamically adaptive tensor-train representations. In the same spirit of all matrix product states, the tensor-train format enables the representation, propagation, and computation of observables of multidimensional wave functions in terms of the grid-based wavepacket tensor components, bypassing the need of actually computing the wave function in its full-rank tensor product grid space. We demonstrate the accuracy and efficiency of the TT-SOFT method as applied to propagation of 24-dimensional wave packets, describing the S 1 /S 2 interconversion dynamics of pyrazine after UV photoexcitation to the S 2 state. Our results show that the TT-SOFT method is a powerful computational approach for simulations of quantum dynamics of polyatomic systems since it avoids the exponential scaling problem of full-rank grid-based representations.

Quantum Tunneling in Testosterone 6β-Hydroxylation by Cytochrome P450: Reaction Dynamics Calculations Employing Multiconfiguration Molecular-Mechanical Potential Energy Surfaces

NASA Astrophysics Data System (ADS)

Zhang, Yan; Lin, Hai

2009-05-01

Testosterone hydroxylation is a prototypical reaction of human cytochrome P450 3A4, which metabolizes about 50% of oral drugs on the market. Reaction dynamics calculations were carried out for the testosterone 6β-hydrogen abstraction and the 6β-d1-testosterone 6β-duterium abstraction employing a model that consists of the substrate and the active oxidant compound I. The calculations were performed at the level of canonical variational transition state theory with multidimensional tunneling and were based on a semiglobal full-dimensional potential energy surface generated by the multiconfiguration molecular mechanics technique. The tunneling coefficients were found to be around 3, indicating substantial contributions by quantum tunneling. However, the tunneling made only modest contributions to the kinetic isotope effects. The kinetic isotope effects were computed to be about 2 in the doublet spin state and about 5 in the quartet spin state.

Reduced chemical kinetic model of detonation combustion of one- and multi-fuel gaseous mixtures with air

NASA Astrophysics Data System (ADS)

Fomin, P. A.

2018-03-01

Two-step approximate models of chemical kinetics of detonation combustion of (i) one hydrocarbon fuel CnHm (for example, methane, propane, cyclohexane etc.) and (ii) multi-fuel gaseous mixtures (∑aiCniHmi) (for example, mixture of methane and propane, synthesis gas, benzene and kerosene) are presented for the first time. The models can be used for any stoichiometry, including fuel/fuels-rich mixtures, when reaction products contain molecules of carbon. Owing to the simplicity and high accuracy, the models can be used in multi-dimensional numerical calculations of detonation waves in corresponding gaseous mixtures. The models are in consistent with the second law of thermodynamics and Le Chatelier's principle. Constants of the models have a clear physical meaning. The models can be used for calculation thermodynamic parameters of the mixture in a state of chemical equilibrium.

Reaction rates and kinetic isotope effects of H{sub 2} + OH → H{sub 2}O + H

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meisner, Jan; Kästner, Johannes, E-mail: kaestner@theochem.uni-stuttgart.de

2016-05-07

We calculated reaction rate constants including atom tunneling of the reaction of dihydrogen with the hydroxy radical down to a temperature of 50 K. Instanton theory and canonical variational theory with microcanonical optimized multidimensional tunneling were applied using a fitted potential energy surface [J. Chen et al., J. Chem. Phys. 138, 154301 (2013)]. All possible protium/deuterium isotopologues were considered. Atom tunneling increases at about 250 K (200 K for deuterium transfer). Even at 50 K the rate constants of all isotopologues remain in the interval 4 ⋅ 10{sup −20} to 4 ⋅ 10{sup −17} cm{sup 3} s{sup −1}, demonstrating thatmore » even deuterated versions of the title reaction are possibly relevant to astrochemical processes in molecular clouds. The transferred hydrogen atom dominates the kinetic isotope effect at all temperatures.« less

Saturation mechanisms of backward stimulated Raman scattering in a one-dimensional geometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Friou, A.; Bénisti, D.; Gremillet, L.

2013-10-15

In this paper, we investigate the saturation mechanisms of backward stimulated Raman scattering (BSRS) induced by nonlinear kinetic effects. In particular, we stress the importance of accounting for both the nonlinear frequency shift of the electron plasma wave and the growth of sidebands, in order to understand what stops the coherent growth of Raman scattering. Using a Bernstein-Greene-Kruskal approach, we provide an estimate for the maximum amplitude reached by a BSRS-driven plasma wave after the phase of monotonic growth. This estimate is in very good agreement with the results from kinetic simulations of stimulated Raman scattering using both a Vlasovmore » and a Particle in Cell code. Our analysis, which may be generalized to a multidimensional geometry, should provide a means to estimate the limits of backward Raman amplification or the effectiveness of strategies that aim at strongly reducing Raman reflectivity in a fusion plasma.« less

Vacuum polarization in the field of a multidimensional global monopole

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grats, Yu. V., E-mail: grats@phys.msu.ru; Spirin, P. A.

2016-11-15

An approximate expression for the Euclidean Green function of a massless scalar field in the spacetime of a multidimensional global monopole has been derived. Expressions for the vacuum expectation values 〈ϕ{sup 2}〉{sub ren} and 〈T{sub 00}〉{sub ren} have been derived by the dimensional regularization method. Comparison with the results obtained by alternative regularization methods is made.

Positivity-preserving numerical schemes for multidimensional advection

NASA Technical Reports Server (NTRS)

Leonard, B. P.; Macvean, M. K.; Lock, A. P.

1993-01-01

This report describes the construction of an explicit, single time-step, conservative, finite-volume method for multidimensional advective flow, based on a uniformly third-order polynomial interpolation algorithm (UTOPIA). Particular attention is paid to the problem of flow-to-grid angle-dependent, anisotropic distortion typical of one-dimensional schemes used component-wise. The third-order multidimensional scheme automatically includes certain cross-difference terms that guarantee good isotropy (and stability). However, above first-order, polynomial-based advection schemes do not preserve positivity (the multidimensional analogue of monotonicity). For this reason, a multidimensional generalization of the first author's universal flux-limiter is sought. This is a very challenging problem. A simple flux-limiter can be found; but this introduces strong anisotropic distortion. A more sophisticated technique, limiting part of the flux and then restoring the isotropy-maintaining cross-terms afterwards, gives more satisfactory results. Test cases are confined to two dimensions; three-dimensional extensions are briefly discussed.

Kinetics of Hydrogen Abstraction and Addition Reactions of 3-Hexene by ȮH Radicals.

PubMed

Yang, Feiyu; Deng, Fuquan; Pan, Youshun; Zhang, Yingjia; Tang, Chenglong; Huang, Zuohua

2017-03-09

Rate coefficients of H atom abstraction and H atom addition reactions of 3-hexene by the hydroxyl radicals were determined using both conventional transition-state theory and canonical variational transition-state theory, with the potential energy surface (PES) evaluated at the CCSD(T)/CBS//BHandHLYP/6-311G(d,p) level and quantum mechanical effect corrected by the compounded methods including one-dimensional Wigner method, multidimensional zero-curvature tunneling method, and small-curvature tunneling method. Results reveal that accounting for approximate 70% of the overall H atom abstractions occur in the allylic site via both direct and indirect channels. The indirect channel containing two van der Waals prereactive complexes exhibits two times larger rate coefficient relative to the direct one. The OH addition reaction also contains two van der Waals complexes, and its submerged barrier results in a negative temperature coefficient behavior at low temperatures. In contrast, The OH addition pathway dominates only at temperatures below 450 K whereas the H atom abstraction reactions dominate overwhelmingly at temperature over 1000 K. All of the rate coefficients calculated with an uncertainty of a factor of 5 were fitted in a quasi-Arrhenius formula. Analyses on the PES, minimum reaction path and activation free Gibbs energy were also performed in this study.

Statistical Relations for Yield Degradation in Inertial Confinement Fusion

NASA Astrophysics Data System (ADS)

Woo, K. M.; Betti, R.; Patel, D.; Gopalaswamy, V.

2017-10-01

In inertial confinement fusion (ICF), the yield-over-clean (YOC) is a quantity commonly used to assess the performance of an implosion with respect to the degradation caused by asymmetries. The YOC also determines the Lawson parameter used to identify the onset of ignition and the level of alpha heating in ICF implosions. In this work, we show that the YOC is a unique function of the residual kinetic energy in the compressed shell (with respect to the 1-D case) regardless of the asymmetry spectrum. This result is derived using a simple model of the deceleration phase as well as through an extensive set of 3-D radiation-hydrodynamics simulations using the code DEC3D. The latter has been recently upgraded to include a 3-D spherical moving mesh, the HYPRE solver for 3-D radiation transport and piecewise-parabolic method for robust shock-capturing hydrodynamic simulations. DEC3D is used to build a synthetic single-mode database to study the behavior of yield degradation caused by Rayleigh-Taylor instabilities in the deceleration phase. The relation between YOC and residual kinetic energy is compared with the result in an adiabatic implosion model. The statistical expression of YOC is also applied to the ignition criterion in the presence of multidimensional nonuniformities. This material is based upon work supported by the Department of Energy National Nuclear Security Administration under Award Number DE-NA0001944.

On Multi-Dimensional Unstructured Mesh Adaption

NASA Technical Reports Server (NTRS)

Wood, William A.; Kleb, William L.

1999-01-01

Anisotropic unstructured mesh adaption is developed for a truly multi-dimensional upwind fluctuation splitting scheme, as applied to scalar advection-diffusion. The adaption is performed locally using edge swapping, point insertion/deletion, and nodal displacements. Comparisons are made versus the current state of the art for aggressive anisotropic unstructured adaption, which is based on a posteriori error estimates. Demonstration of both schemes to model problems, with features representative of compressible gas dynamics, show the present method to be superior to the a posteriori adaption for linear advection. The performance of the two methods is more similar when applied to nonlinear advection, with a difference in the treatment of shocks. The a posteriori adaption can excessively cluster points to a shock, while the present multi-dimensional scheme tends to merely align with a shock, using fewer nodes. As a consequence of this alignment tendency, an implementation of eigenvalue limiting for the suppression of expansion shocks is developed for the multi-dimensional distribution scheme. The differences in the treatment of shocks by the adaption schemes, along with the inherently low levels of artificial dissipation in the fluctuation splitting solver, suggest the present method is a strong candidate for applications to compressible gas dynamics.

Assessing Dimensionality of Noncompensatory Multidimensional Item Response Theory with Complex Structures

ERIC Educational Resources Information Center

Svetina, Dubravka

2013-01-01

The purpose of this study was to investigate the effect of complex structure on dimensionality assessment in noncompensatory multidimensional item response models using dimensionality assessment procedures based on DETECT (dimensionality evaluation to enumerate contributing traits) and NOHARM (normal ogive harmonic analysis robust method). Five…

A New Heterogeneous Multidimensional Unfolding Procedure

ERIC Educational Resources Information Center

Park, Joonwook; Rajagopal, Priyali; DeSarbo, Wayne S.

2012-01-01

A variety of joint space multidimensional scaling (MDS) methods have been utilized for the spatial analysis of two- or three-way dominance data involving subjects' preferences, choices, considerations, intentions, etc. so as to provide a parsimonious spatial depiction of the underlying relevant dimensions, attributes, stimuli, and/or subjects'…

The Cognitive Visualization System with the Dynamic Projection of Multidimensional Data

NASA Astrophysics Data System (ADS)

Gorohov, V.; Vitkovskiy, V.

2008-08-01

The phenomenon of cognitive machine drawing consists in the generation on the screen the special graphic representations, which create in the brain of human operator entertainment means. These means seem man by aesthetically attractive and, thus, they stimulate its descriptive imagination, closely related to the intuitive mechanisms of thinking. The essence of cognitive effect lies in the fact that man receives the moving projection as pseudo-three-dimensional object characterizing multidimensional means in the multidimensional space. After the thorough qualitative study of the visual aspects of multidimensional means with the aid of the enumerated algorithms appears the possibility, using algorithms of standard machine drawing to paint the interesting user separate objects or the groups of objects. Then it is possible to again return to the dynamic behavior of the rotation of means for the purpose of checking the intuitive ideas of user about the clusters and the connections in multidimensional data. Is possible the development of the methods of cognitive machine drawing in combination with other information technologies, first of all with the packets of digital processing of images and multidimensional statistical analysis.

Imaging energy landscapes with concentrated diffusing colloidal probes

NASA Astrophysics Data System (ADS)

Bahukudumbi, Pradipkumar; Bevan, Michael A.

2007-06-01

The ability to locally interrogate interactions between particles and energetically patterned surfaces provides essential information to design, control, and optimize template directed self-assembly processes. Although numerous techniques are capable of characterizing local physicochemical surface properties, no current method resolves interactions between colloids and patterned surfaces on the order of the thermal energy kT, which is the inherent energy scale of equilibrium self-assembly processes. Here, the authors describe video microscopy measurements and an inverse Monte Carlo analysis of diffusing colloidal probes as a means to image three dimensional free energy and potential energy landscapes due to physically patterned surfaces. In addition, they also develop a consistent analysis of self-diffusion in inhomogeneous fluids of concentrated diffusing probes on energy landscapes, which is important to the temporal imaging process and to self-assembly kinetics. Extension of the concepts developed in this work suggests a general strategy to image multidimensional and multiscale physical, chemical, and biological surfaces using a variety of diffusing probes (i.e., molecules, macromolecules, nanoparticles, and colloids).

Cuba: Multidimensional numerical integration library

NASA Astrophysics Data System (ADS)

Hahn, Thomas

2016-08-01

The Cuba library offers four independent routines for multidimensional numerical integration: Vegas, Suave, Divonne, and Cuhre. The four algorithms work by very different methods, and can integrate vector integrands and have very similar Fortran, C/C++, and Mathematica interfaces. Their invocation is very similar, making it easy to cross-check by substituting one method by another. For further safeguarding, the output is supplemented by a chi-square probability which quantifies the reliability of the error estimate.

The Multidimensionality of Child Poverty: Evidence from Afghanistan

ERIC Educational Resources Information Center

Trani, Jean-Francois; Biggeri, Mario; Mauro, Vincenzo

2013-01-01

This paper examines multidimensional poverty among children in Afghanistan using the Alkire-Foster method. Several previous studies have underlined the need to separate children from their adult nexus when studying poverty and treat them according to their own specificities. From the capability approach, child poverty is understood to be the lack…

Avoiding Degeneracy in Multidimensional Unfolding by Penalizing on the Coefficient of Variation

ERIC Educational Resources Information Center

Busing, Frank M. T. A.; Groenen, Patrick J. K.; Heiser, Willem J.

2005-01-01

Multidimensional unfolding methods suffer from the degeneracy problem in almost all circumstances. Most degeneracies are easily recognized: the solutions are perfect but trivial, characterized by approximately equal distances between points from different sets. A definition of an absolutely degenerate solution is proposed, which makes clear that…

Multidimensional Scaling of High School Students' Perceptions of Academic Dishonesty

ERIC Educational Resources Information Center

Schmelkin, Liora Pedhazur; Gilbert, Kimberly A.; Silva, Rebecca

2010-01-01

Although cheating on tests and other forms of academic dishonesty are considered rampant, no standard definition of academic dishonesty exists. The current study was conducted to investigate the perceptions of academic dishonesty in high school students, utilizing an innovative methodology, multidimensional scaling (MDS). Two methods were used to…

Application of Multi-Parameter Data Visualization by Means of Multidimensional Scaling to Evaluate Possibility of Coal Gasification

NASA Astrophysics Data System (ADS)

Jamróz, Dariusz; Niedoba, Tomasz; Surowiak, Agnieszka; Tumidajski, Tadeusz; Szostek, Roman; Gajer, Mirosław

2017-09-01

The application of methods drawing upon multi-parameter visualization of data by transformation of multidimensional space into two-dimensional one allow to show multi-parameter data on computer screen. Thanks to that, it is possible to conduct a qualitative analysis of this data in the most natural way for human being, i.e. by the sense of sight. An example of such method of multi-parameter visualization is multidimensional scaling. This method was used in this paper to present and analyze a set of seven-dimensional data obtained from Janina Mining Plant and Wieczorek Coal Mine. It was decided to examine whether the method of multi-parameter data visualization allows to divide the samples space into areas of various applicability to fluidal gasification process. The "Technological applicability card for coals" was used for this purpose [Sobolewski et al., 2012; 2017], in which the key parameters, important and additional ones affecting the gasification process were described.

Fast acquisition of multidimensional NMR spectra of solids and mesophases using alternative sampling methods.

PubMed

Lesot, Philippe; Kazimierczuk, Krzysztof; Trébosc, Julien; Amoureux, Jean-Paul; Lafon, Olivier

2015-11-01

Unique information about the atom-level structure and dynamics of solids and mesophases can be obtained by the use of multidimensional nuclear magnetic resonance (NMR) experiments. Nevertheless, the acquisition of these experiments often requires long acquisition times. We review here alternative sampling methods, which have been proposed to circumvent this issue in the case of solids and mesophases. Compared to the spectra of solutions, those of solids and mesophases present some specificities because they usually display lower signal-to-noise ratios, non-Lorentzian line shapes, lower spectral resolutions and wider spectral widths. We highlight herein the advantages and limitations of these alternative sampling methods. A first route to accelerate the acquisition time of multidimensional NMR spectra consists in the use of sparse sampling schemes, such as truncated, radial or random sampling ones. These sparsely sampled datasets are generally processed by reconstruction methods differing from the Discrete Fourier Transform (DFT). A host of non-DFT methods have been applied for solids and mesophases, including the G-matrix Fourier transform, the linear least-square procedures, the covariance transform, the maximum entropy and the compressed sensing. A second class of alternative sampling consists in departing from the Jeener paradigm for multidimensional NMR experiments. These non-Jeener methods include Hadamard spectroscopy as well as spatial or orientational encoding of the evolution frequencies. The increasing number of high field NMR magnets and the development of techniques to enhance NMR sensitivity will contribute to widen the use of these alternative sampling methods for the study of solids and mesophases in the coming years. Copyright © 2015 John Wiley & Sons, Ltd.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Minghai; Duan, Mojie; Fan, Jue

The thermodynamics and kinetics of protein folding and protein conformational changes are governed by the underlying free energy landscape. However, the multidimensional nature of the free energy landscape makes it difficult to describe. We propose to use a weighted-graph approach to depict the free energy landscape with the nodes on the graph representing the conformational states and the edge weights reflecting the free energy barriers between the states. Our graph is constructed from a molecular dynamics trajectory and does not involve projecting the multi-dimensional free energy landscape onto a low-dimensional space defined by a few order parameters. The calculation ofmore » free energy barriers was based on transition-path theory using the MSMBuilder2 package. We compare our graph with the widely used transition disconnectivity graph (TRDG) which is constructed from the same trajectory and show that our approach gives more accurate description of the free energy landscape than the TRDG approach even though the latter can be organized into a simple tree representation. The weighted-graph is a general approach and can be used on any complex system.« less

Free-Energy Landscape and Proton Transfer Pathways in Oxidative Deamination by Methylamine Dehydrogenase.

PubMed

Zelleke, Theodros; Marx, Dominik

2017-01-18

The rate-determining step in the reductive half-reaction of the bacterial enzyme methylamine dehydrogenase, which is proton abstraction from the native substrate methylamine, is investigated using accelerated QM/MM molecular dynamics simulations at room temperature. Generation of the multidimensional thermal free-energy landscape without restriction of the degrees of freedom beyond a multidimensional reaction subspace maps two rather similar pathways for the underlying proton transfer to one of two aspartate carboxyl oxygen atoms, termed OD1 and OD2, which hydrogen bond with Thr122 and Trp108, respectively. Despite significant large-amplitude motion perpendicular to the one-dimensional proton transfer coordinate, due to fluctuations of the donor-acceptor distance of about 3 Å, it is found that the one-dimensional proton transfer free-energy profiles are essentially identical to the minimum free-energy pathways on the multidimensional free-energy landscapes for both proton transfer channels. Proton transfer to one of the acceptor oxygen atoms-the OD2 site-is slightly favored in methylamine dehydrogenase by approximately 2 kcal mol -1 , both kinetically and thermodynamically. Mechanistic analyses reveal that the hydrogen bond between Thr122β and OD1 is always present in the transition state independently of the proton transfer channel. Population analysis confirms that the electronic charge gained upon oxidation of the substrate is delocalized within the ring systems of the tryptophan tryptophylquinone cofactor. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Detailed Multidimensional Simulations of the Structure and Dynamics of Flames

NASA Technical Reports Server (NTRS)

Patnaik, G.; Kailasanath, K.

1999-01-01

Numerical simulations in which the various physical and chemical processes can be independently controlled can significantly advance our understanding of the structure, stability, dynamics and extinction of flames. Therefore, our approach has been to use detailed time-dependent, multidimensional, multispecies numerical models to perform carefully designed computational experiments of flames on Earth and in microgravity environments. Some of these computational experiments are complementary to physical experiments performed under the Microgravity Program while others provide a fundamental understanding that cannot be obtained from physical experiments alone. In this report, we provide a brief summary of our recent research highlighting the contributions since the previous microgravity combustion workshop. There are a number of mechanisms that can cause flame instabilities and result in the formation of dynamic multidimensional structures. In the past, we have used numerical simulations to show that it is the thermo-diffusive instability rather than an instability due to preferential diffusion that is the dominant mechanism for the formation of cellular flames in lean hydrogen-air mixtures. Other studies have explored the role of gravity on flame dynamics and extinguishment, multi-step kinetics and radiative losses on flame instabilities in rich hydrogen-air flames, and heat losses on burner-stabilized flames in microgravity. The recent emphasis of our work has been on exploring flame-vortex interactions and further investigating the structure and dynamics of lean hydrogen-air flames in microgravity. These topics are briefly discussed after a brief discussion of our computational approach for solving these problems.

The Evaluation of Classroom Social Structure by Three-Way Multidimensional Scaling of Sociometric Data.

ERIC Educational Resources Information Center

Langeheine, Rolf

1978-01-01

A three-way multidimensional scaling model is presented as a method for identifying classroom cliques, by simultaneous analysis of three variables (for example, chooser/choosen/criteria). Two scaling models--Carroll and Chang's INDSCAL and Lingoes' PINDIS--are presented and applied to two sets of empirical data. (CP)

Evaluating Change in Behavioral Preferences: Multidimensional Scaling Single-Ideal Point Model

ERIC Educational Resources Information Center

Ding, Cody

2016-01-01

The purpose of the article is to propose a multidimensional scaling single-ideal point model as a method to evaluate changes in individuals' preferences under the explicit methodological framework of behavioral preference assessment. One example is used to illustrate the approach for a clear idea of what this approach can accomplish.

Comparing the Performance of Five Multidimensional CAT Selection Procedures with Different Stopping Rules

ERIC Educational Resources Information Center

Yao, Lihua

2013-01-01

Through simulated data, five multidimensional computerized adaptive testing (MCAT) selection procedures with varying test lengths are examined and compared using different stopping rules. Fixed item exposure rates are used for all the items, and the Priority Index (PI) method is used for the content constraints. Two stopping rules, standard error…

Income and beyond: Multidimensional Poverty in Six Latin American Countries

ERIC Educational Resources Information Center

Battiston, Diego; Cruces, Guillermo; Lopez-Calva, Luis Felipe; Lugo, Maria Ana; Santos, Maria Emma

2013-01-01

This paper studies multidimensional poverty for Argentina, Brazil, Chile, El Salvador, Mexico and Uruguay for the period 1992-2006. The approach overcomes the limitations of the two traditional methods of poverty analysis in Latin America (income-based and unmet basic needs) by combining income with five other dimensions: school attendance for…

Comparing Voice-Therapy and Vocal-Hygiene Treatments in Dysphonia Using a Limited Multidimensional Evaluation Protocol

ERIC Educational Resources Information Center

Rodriguez-Parra, Maria J.; Adrian, Jose A.; Casado, Juan C.

2011-01-01

Purpose: This study evaluates the effectiveness of two different programs of voice-treatment on a heterogeneous group of dysphonic speakers and the stability of therapeutic progress for longterm follow-up post-treatment period, using a limited multidimensional protocol of evaluation. Method: Forty-two participants with voice disorders were…

Assessing Fit and Dimensionality in Least Squares Metric Multidimensional Scaling Using Akaike's Information Criterion

ERIC Educational Resources Information Center

Ding, Cody S.; Davison, Mark L.

2010-01-01

Akaike's information criterion is suggested as a tool for evaluating fit and dimensionality in metric multidimensional scaling that uses least squares methods of estimation. This criterion combines the least squares loss function with the number of estimated parameters. Numerical examples are presented. The results from analyses of both simulation…

A Multi-Method Multi-Analytic Approach to Establishing Internal Construct Validity Evidence: The Sport Multidimensional Perfectionism Scale 2

ERIC Educational Resources Information Center

Gotwals, John K.; Dunn, John G. H.

2009-01-01

This article presents a chronology of three empirical studies that outline the measurement process by which two new subscales ("Doubts about Actions" and "Organization") were developed and integrated into a revised version of Dunn, Causgrove Dunn, and Syrotuik's (2002) "Sport Multidimensional Perfectionism Scale"…

Heuristic Constraint Management Methods in Multidimensional Adaptive Testing

ERIC Educational Resources Information Center

Born, Sebastian; Frey, Andreas

2017-01-01

Although multidimensional adaptive testing (MAT) has been proven to be highly advantageous with regard to measurement efficiency when several highly correlated dimensions are measured, there are few operational assessments that use MAT. This may be due to issues of constraint management, which is more complex in MAT than it is in unidimensional…

Large-scale Instability during Gravitational Collapse with Neutrino Transport and a Core-Collapse Supernova

NASA Astrophysics Data System (ADS)

Aksenov, A. G.; Chechetkin, V. M.

2018-04-01

Most of the energy released in the gravitational collapse of the cores of massive stars is carried away by neutrinos. Neutrinos play a pivotal role in explaining core-collape supernovae. Currently, mathematical models of the gravitational collapse are based on multi-dimensional gas dynamics and thermonuclear reactions, while neutrino transport is considered in a simplified way. Multidimensional gas dynamics is used with neutrino transport in the flux-limited diffusion approximation to study the role of multi-dimensional effects. The possibility of large-scale convection is discussed, which is interesting both for explaining SN II and for setting up observations to register possible high-energy (≳10MeV) neutrinos from the supernova. A new multi-dimensional, multi-temperature gas dynamics method with neutrino transport is presented.

Multidimensional Recurrence Quantification Analysis (MdRQA) for the Analysis of Multidimensional Time-Series: A Software Implementation in MATLAB and Its Application to Group-Level Data in Joint Action

PubMed Central

Wallot, Sebastian; Roepstorff, Andreas; Mønster, Dan

2016-01-01

We introduce Multidimensional Recurrence Quantification Analysis (MdRQA) as a tool to analyze multidimensional time-series data. We show how MdRQA can be used to capture the dynamics of high-dimensional signals, and how MdRQA can be used to assess coupling between two or more variables. In particular, we describe applications of the method in research on joint and collective action, as it provides a coherent analysis framework to systematically investigate dynamics at different group levels—from individual dynamics, to dyadic dynamics, up to global group-level of arbitrary size. The Appendix in Supplementary Material contains a software implementation in MATLAB to calculate MdRQA measures. PMID:27920748

Multidimensional Recurrence Quantification Analysis (MdRQA) for the Analysis of Multidimensional Time-Series: A Software Implementation in MATLAB and Its Application to Group-Level Data in Joint Action.

PubMed

Wallot, Sebastian; Roepstorff, Andreas; Mønster, Dan

2016-01-01

We introduce Multidimensional Recurrence Quantification Analysis (MdRQA) as a tool to analyze multidimensional time-series data. We show how MdRQA can be used to capture the dynamics of high-dimensional signals, and how MdRQA can be used to assess coupling between two or more variables. In particular, we describe applications of the method in research on joint and collective action, as it provides a coherent analysis framework to systematically investigate dynamics at different group levels-from individual dynamics, to dyadic dynamics, up to global group-level of arbitrary size. The Appendix in Supplementary Material contains a software implementation in MATLAB to calculate MdRQA measures.

The necessity-concerns framework: a multidimensional theory benefits from multidimensional analysis.

PubMed

Phillips, L Alison; Diefenbach, Michael A; Kronish, Ian M; Negron, Rennie M; Horowitz, Carol R

2014-08-01

Patients' medication-related concerns and necessity-beliefs predict adherence. Evaluation of the potentially complex interplay of these two dimensions has been limited because of methods that reduce them to a single dimension (difference scores). We use polynomial regression to assess the multidimensional effect of stroke-event survivors' medication-related concerns and necessity beliefs on their adherence to stroke-prevention medication. Survivors (n = 600) rated their concerns, necessity beliefs, and adherence to medication. Confirmatory and exploratory polynomial regression determined the best-fitting multidimensional model. As posited by the necessity-concerns framework (NCF), the greatest and lowest adherence was reported by those necessity weak concerns and strong concerns/weak Necessity-Beliefs, respectively. However, as could not be assessed using a difference-score model, patients with ambivalent beliefs were less adherent than those exhibiting indifference. Polynomial regression allows for assessment of the multidimensional nature of the NCF. Clinicians/Researchers should be aware that concerns and necessity dimensions are not polar opposites.

Simulation of 2D Kinetic Effects in Plasmas using the Grid Based Continuum Code LOKI

NASA Astrophysics Data System (ADS)

Banks, Jeffrey; Berger, Richard; Chapman, Tom; Brunner, Stephan

2016-10-01

Kinetic simulation of multi-dimensional plasma waves through direct discretization of the Vlasov equation is a useful tool to study many physical interactions and is particularly attractive for situations where minimal fluctuation levels are desired, for instance, when measuring growth rates of plasma wave instabilities. However, direct discretization of phase space can be computationally expensive, and as a result there are few examples of published results using Vlasov codes in more than a single configuration space dimension. In an effort to fill this gap we have developed the Eulerian-based kinetic code LOKI that evolves the Vlasov-Poisson system in 2+2-dimensional phase space. The code is designed to reduce the cost of phase-space computation by using fully 4th order accurate conservative finite differencing, while retaining excellent parallel scalability that efficiently uses large scale computing resources. In this poster I will discuss the algorithms used in the code as well as some aspects of their parallel implementation using MPI. I will also overview simulation results of basic plasma wave instabilities relevant to laser plasma interaction, which have been obtained using the code.

A 3D finite element ALE method using an approximate Riemann solution

DOE PAGES

Chiravalle, V. P.; Morgan, N. R.

2016-08-09

Arbitrary Lagrangian–Eulerian finite volume methods that solve a multidimensional Riemann-like problem at the cell center in a staggered grid hydrodynamic (SGH) arrangement have been proposed. This research proposes a new 3D finite element arbitrary Lagrangian–Eulerian SGH method that incorporates a multidimensional Riemann-like problem. Here, two different Riemann jump relations are investigated. A new limiting method that greatly improves the accuracy of the SGH method on isentropic flows is investigated. A remap method that improves upon a well-known mesh relaxation and remapping technique in order to ensure total energy conservation during the remap is also presented. Numerical details and test problemmore » results are presented.« less

A 3D finite element ALE method using an approximate Riemann solution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiravalle, V. P.; Morgan, N. R.

Arbitrary Lagrangian–Eulerian finite volume methods that solve a multidimensional Riemann-like problem at the cell center in a staggered grid hydrodynamic (SGH) arrangement have been proposed. This research proposes a new 3D finite element arbitrary Lagrangian–Eulerian SGH method that incorporates a multidimensional Riemann-like problem. Here, two different Riemann jump relations are investigated. A new limiting method that greatly improves the accuracy of the SGH method on isentropic flows is investigated. A remap method that improves upon a well-known mesh relaxation and remapping technique in order to ensure total energy conservation during the remap is also presented. Numerical details and test problemmore » results are presented.« less

Generalizing DTW to the multi-dimensional case requires an adaptive approach

PubMed Central

Hu, Bing; Jin, Hongxia; Wang, Jun; Keogh, Eamonn

2017-01-01

In recent years Dynamic Time Warping (DTW) has emerged as the distance measure of choice for virtually all time series data mining applications. For example, virtually all applications that process data from wearable devices use DTW as a core sub-routine. This is the result of significant progress in improving DTW’s efficiency, together with multiple empirical studies showing that DTW-based classifiers at least equal (and generally surpass) the accuracy of all their rivals across dozens of datasets. Thus far, most of the research has considered only the one-dimensional case, with practitioners generalizing to the multi-dimensional case in one of two ways, dependent or independent warping. In general, it appears the community believes either that the two ways are equivalent, or that the choice is irrelevant. In this work, we show that this is not the case. The two most commonly used multi-dimensional DTW methods can produce different classifications, and neither one dominates over the other. This seems to suggest that one should learn the best method for a particular application. However, we will show that this is not necessary; a simple, principled rule can be used on a case-by-case basis to predict which of the two methods we should trust at the time of classification. Our method allows us to ensure that classification results are at least as accurate as the better of the two rival methods, and, in many cases, our method is significantly more accurate. We demonstrate our ideas with the most extensive set of multi-dimensional time series classification experiments ever attempted. PMID:29104448

A solvable model of Vlasov-kinetic plasma turbulence in Fourier-Hermite phase space

NASA Astrophysics Data System (ADS)

Adkins, T.; Schekochihin, A. A.

2018-02-01

A class of simple kinetic systems is considered, described by the one-dimensional Vlasov-Landau equation with Poisson or Boltzmann electrostatic response and an energy source. Assuming a stochastic electric field, a solvable model is constructed for the phase-space turbulence of the particle distribution. The model is a kinetic analogue of the Kraichnan-Batchelor model of chaotic advection. The solution of the model is found in Fourier-Hermite space and shows that the free-energy flux from low to high Hermite moments is suppressed, with phase mixing cancelled on average by anti-phase-mixing (stochastic plasma echo). This implies that Landau damping is an ineffective route to dissipation (i.e. to thermalisation of electric energy via velocity space). The full Fourier-Hermite spectrum is derived. Its asymptotics are -3/2$ at low wavenumbers and high Hermite moments ( ) and -1/2k-2$ at low Hermite moments and high wavenumbers ( ). These conclusions hold at wavenumbers below a certain cutoff (analogue of Kolmogorov scale), which increases with the amplitude of the stochastic electric field and scales as inverse square of the collision rate. The energy distribution and flows in phase space are a simple and, therefore, useful example of competition between phase mixing and nonlinear dynamics in kinetic turbulence, reminiscent of more realistic but more complicated multi-dimensional systems that have not so far been amenable to complete analytical solution.

Multidimensional signal modulation and/or demodulation for data communications

DOEpatents

Smith, Stephen F [London, TN; Dress, William B [Camas, WA

2008-03-04

Systems and methods are described for multidimensional signal modulation and/or demodulation for data communications. A method includes modulating a carrier signal in a first domain selected from the group consisting of phase, frequency, amplitude, polarization and spread; modulating the carrier signal in a second domain selected from the group consisting of phase, frequency, amplitude, polarization and spread; and modulating the carrier signal in a third domain selected from the group consisting of phase, frequency, amplitude, polarization and spread.

A Method for Generating Reduced-Order Linear Models of Multidimensional Supersonic Inlets

NASA Technical Reports Server (NTRS)

Chicatelli, Amy; Hartley, Tom T.

1998-01-01

Simulation of high speed propulsion systems may be divided into two categories, nonlinear and linear. The nonlinear simulations are usually based on multidimensional computational fluid dynamics (CFD) methodologies and tend to provide high resolution results that show the fine detail of the flow. Consequently, these simulations are large, numerically intensive, and run much slower than real-time. ne linear simulations are usually based on large lumping techniques that are linearized about a steady-state operating condition. These simplistic models often run at or near real-time but do not always capture the detailed dynamics of the plant. Under a grant sponsored by the NASA Lewis Research Center, Cleveland, Ohio, a new method has been developed that can be used to generate improved linear models for control design from multidimensional steady-state CFD results. This CFD-based linear modeling technique provides a small perturbation model that can be used for control applications and real-time simulations. It is important to note the utility of the modeling procedure; all that is needed to obtain a linear model of the propulsion system is the geometry and steady-state operating conditions from a multidimensional CFD simulation or experiment. This research represents a beginning step in establishing a bridge between the controls discipline and the CFD discipline so that the control engineer is able to effectively use multidimensional CFD results in control system design and analysis.

Method of multi-dimensional moment analysis for the characterization of signal peaks

DOEpatents

Pfeifer, Kent B; Yelton, William G; Kerr, Dayle R; Bouchier, Francis A

2012-10-23

A method of multi-dimensional moment analysis for the characterization of signal peaks can be used to optimize the operation of an analytical system. With a two-dimensional Peclet analysis, the quality and signal fidelity of peaks in a two-dimensional experimental space can be analyzed and scored. This method is particularly useful in determining optimum operational parameters for an analytical system which requires the automated analysis of large numbers of analyte data peaks. For example, the method can be used to optimize analytical systems including an ion mobility spectrometer that uses a temperature stepped desorption technique for the detection of explosive mixtures.

Multidimensional poverty and child survival in India.

PubMed

Mohanty, Sanjay K

2011-01-01

Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. OBJECTIVES AND METHODOLOGY: Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population.

From Molecules to Cells to Organisms: Understanding Health and Disease with Multidimensional Single-Cell Methods

NASA Astrophysics Data System (ADS)

Candia, Julián

2013-03-01

The multidimensional nature of many single-cell measurements (e.g. multiple markers measured simultaneously using Fluorescence-Activated Cell Sorting (FACS) technologies) offers unprecedented opportunities to unravel emergent phenomena that are governed by the cooperative action of multiple elements across different scales, from molecules and proteins to cells and organisms. We will discuss an integrated analysis framework to investigate multicolor FACS data from different perspectives: Singular Value Decomposition to achieve an effective dimensional reduction in the data representation, machine learning techniques to separate different patient classes and improve diagnosis, as well as a novel cell-similarity network analysis method to identify cell subpopulations in an unbiased manner. Besides FACS data, this framework is versatile: in this vein, we will demonstrate an application to the multidimensional single-cell shape analysis of healthy and prematurely aged cells.

A second-order cell-centered Lagrangian ADER-MOOD finite volume scheme on multidimensional unstructured meshes for hydrodynamics

NASA Astrophysics Data System (ADS)

Boscheri, Walter; Dumbser, Michael; Loubère, Raphaël; Maire, Pierre-Henri

2018-04-01

In this paper we develop a conservative cell-centered Lagrangian finite volume scheme for the solution of the hydrodynamics equations on unstructured multidimensional grids. The method is derived from the Eucclhyd scheme discussed in [47,43,45]. It is second-order accurate in space and is combined with the a posteriori Multidimensional Optimal Order Detection (MOOD) limiting strategy to ensure robustness and stability at shock waves. Second-order of accuracy in time is achieved via the ADER (Arbitrary high order schemes using DERivatives) approach. A large set of numerical test cases is proposed to assess the ability of the method to achieve effective second order of accuracy on smooth flows, maintaining an essentially non-oscillatory behavior on discontinuous profiles, general robustness ensuring physical admissibility of the numerical solution, and precision where appropriate.

Numerical Simulations of Multidimensional Flows in Presence of either Strong Shocks or Strong Gravitational Fields

NASA Astrophysics Data System (ADS)

Font, J. A.; Ibanez, J. M.; Marti, J. M.

1993-04-01

Some numerical solutions via local characteristic approach have been obtained describing multidimensional flows. These solutions have been used as tests of a two- dimensional code which extends some high-resolution shock-captunng methods, designed recently to solve nonlinear hyperbolic systems of conservation laws. K words: HYDRODYNAMICS - BLACK HOLE - RELATIVITY - SHOCK WAVES

Multidimensional CAT Item Selection Methods for Domain Scores and Composite Scores: Theory and Applications

ERIC Educational Resources Information Center

Yao, Lihua

2012-01-01

Multidimensional computer adaptive testing (MCAT) can provide higher precision and reliability or reduce test length when compared with unidimensional CAT or with the paper-and-pencil test. This study compared five item selection procedures in the MCAT framework for both domain scores and overall scores through simulation by varying the structure…

A Bifactor Multidimensional Item Response Theory Model for Differential Item Functioning Analysis on Testlet-Based Items

ERIC Educational Resources Information Center

Fukuhara, Hirotaka; Kamata, Akihito

2011-01-01

A differential item functioning (DIF) detection method for testlet-based data was proposed and evaluated in this study. The proposed DIF model is an extension of a bifactor multidimensional item response theory (MIRT) model for testlets. Unlike traditional item response theory (IRT) DIF models, the proposed model takes testlet effects into…

Students' Personal Connection with Science: Investigating the Multidimensional Phenomenological Structure of Self-Relevance

ERIC Educational Resources Information Center

Hartwell, Matthew; Kaplan, Avi

2018-01-01

This paper presents findings from a two-phase mixed methods study investigating the phenomenological structure of self-relevance among ninth-grade junior high school biology students (Phase 1: N = 118; Phase 2: N = 139). We begin with a phenomenological multidimensional definition of self-relevance as comprising three dimensions: the academic…

Effectiveness of Multidimensional Family Therapy with Higher Severity Substance-Abusing Adolescents: Report from Two Randomized Controlled Trials

ERIC Educational Resources Information Center

Henderson, Craig E.; Dakof, Gayle A.; Greenbaum, Paul E.; Liddle, Howard A.

2010-01-01

Objective: We used growth mixture modeling to examine heterogeneity in treatment response in a secondary analysis of 2 randomized controlled trials testing multidimensional family therapy (MDFT), an established evidence-based therapy for adolescent drug abuse and delinquency. Method: The first study compared 2 evidence-based adolescent substance…

Bayesian Analysis of Multidimensional Item Response Theory Models: A Discussion and Illustration of Three Response Style Models

ERIC Educational Resources Information Center

Leventhal, Brian C.; Stone, Clement A.

2018-01-01

Interest in Bayesian analysis of item response theory (IRT) models has grown tremendously due to the appeal of the paradigm among psychometricians, advantages of these methods when analyzing complex models, and availability of general-purpose software. Possible models include models which reflect multidimensionality due to designed test structure,…

Multidimensional electron beam-plasma instabilities in the relativistic regime

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bret, A.; Gremillet, L.; Dieckmann, M. E.

2010-12-15

The interest in relativistic beam-plasma instabilities has been greatly rejuvenated over the past two decades by novel concepts in laboratory and space plasmas. Recent advances in this long-standing field are here reviewed from both theoretical and numerical points of view. The primary focus is on the two-dimensional spectrum of unstable electromagnetic waves growing within relativistic, unmagnetized, and uniform electron beam-plasma systems. Although the goal is to provide a unified picture of all instability classes at play, emphasis is put on the potentially dominant waves propagating obliquely to the beam direction, which have received little attention over the years. First, themore » basic derivation of the general dielectric function of a kinetic relativistic plasma is recalled. Next, an overview of two-dimensional unstable spectra associated with various beam-plasma distribution functions is given. Both cold-fluid and kinetic linear theory results are reported, the latter being based on waterbag and Maxwell-Juettner model distributions. The main properties of the competing modes (developing parallel, transverse, and oblique to the beam) are given, and their respective region of dominance in the system parameter space is explained. Later sections address particle-in-cell numerical simulations and the nonlinear evolution of multidimensional beam-plasma systems. The elementary structures generated by the various instability classes are first discussed in the case of reduced-geometry systems. Validation of linear theory is then illustrated in detail for large-scale systems, as is the multistaged character of the nonlinear phase. Finally, a collection of closely related beam-plasma problems involving additional physical effects is presented, and worthwhile directions of future research are outlined.« less

Computational study of the reactions of methanol with the hydroperoxyl and methyl radicals. 2. Accurate thermal rate constants.

PubMed

Alecu, I M; Truhlar, Donald G

2011-12-29

Multistructural canonical variational-transition-state theory with multidimensional tunneling (MS-CVT/MT) is employed to calculate thermal rate constants for the abstraction of hydrogen atoms from both positions of methanol by the hydroperoxyl and methyl radicals over the temperature range 100-3000 K. The M08-HX hybrid meta-generalized gradient approximation density functional and M08-HX with specific reaction parameters, both with the maug-cc-pVTZ basis set, were validated in part 1 of this study (Alecu, I. M.; Truhlar, D. G. J. Phys. Chem. A2011, 115, 2811) against highly accurate CCSDT(2)(Q)/CBS calculations for the energetics of these reactions, and they are used here to compute the properties of all stationary points and the energies, gradients, and Hessians of nonstationary points along each considered reaction path. The internal rotations in some of the transition states are found to be highly anharmonic and strongly coupled to each other, and they generate multiple structures (conformations) whose contributions are included in the partition function. It is shown that the previous estimates for these rate constants used to build kinetic models for the combustion of methanol, some of which were based on transition state theory calculations with one-dimensional tunneling corrections and harmonic-oscillator approximations or separable one-dimensional hindered rotor treatments of torsions, are appreciably different than the ones presently calculated using MS-CVT/MT. The rate constants obtained from the best MS-CVT/MT calculations carried out in this study, in which the important effects of corner cutting due to small and large reaction path curvature are captured via a microcanonical optimized multidimensional tunneling (μOMT) treatment, are recommended for future refinement of the kinetic model for methanol combustion. © 2011 American Chemical Society

A versatile embedded boundary adaptive mesh method for compressible flow in complex geometry

NASA Astrophysics Data System (ADS)

Al-Marouf, M.; Samtaney, R.

2017-05-01

We present an embedded ghost fluid method for numerical solutions of the compressible Navier Stokes (CNS) equations in arbitrary complex domains. A PDE multidimensional extrapolation approach is used to reconstruct the solution in the ghost fluid regions and imposing boundary conditions on the fluid-solid interface, coupled with a multi-dimensional algebraic interpolation for freshly cleared cells. The CNS equations are numerically solved by the second order multidimensional upwind method. Block-structured adaptive mesh refinement, implemented with the Chombo framework, is utilized to reduce the computational cost while keeping high resolution mesh around the embedded boundary and regions of high gradient solutions. The versatility of the method is demonstrated via several numerical examples, in both static and moving geometry, ranging from low Mach number nearly incompressible flows to supersonic flows. Our simulation results are extensively verified against other numerical results and validated against available experimental results where applicable. The significance and advantages of our implementation, which revolve around balancing between the solution accuracy and implementation difficulties, are briefly discussed as well.

Self-Learning Adaptive Umbrella Sampling Method for the Determination of Free Energy Landscapes in Multiple Dimensions

PubMed Central

Wojtas-Niziurski, Wojciech; Meng, Yilin; Roux, Benoit; Bernèche, Simon

2013-01-01

The potential of mean force describing conformational changes of biomolecules is a central quantity that determines the function of biomolecular systems. Calculating an energy landscape of a process that depends on three or more reaction coordinates might require a lot of computational power, making some of multidimensional calculations practically impossible. Here, we present an efficient automatized umbrella sampling strategy for calculating multidimensional potential of mean force. The method progressively learns by itself, through a feedback mechanism, which regions of a multidimensional space are worth exploring and automatically generates a set of umbrella sampling windows that is adapted to the system. The self-learning adaptive umbrella sampling method is first explained with illustrative examples based on simplified reduced model systems, and then applied to two non-trivial situations: the conformational equilibrium of the pentapeptide Met-enkephalin in solution and ion permeation in the KcsA potassium channel. With this method, it is demonstrated that a significant smaller number of umbrella windows needs to be employed to characterize the free energy landscape over the most relevant regions without any loss in accuracy. PMID:23814508

Seismic interferometry by multidimensional deconvolution as a means to compensate for anisotropic illumination

NASA Astrophysics Data System (ADS)

Wapenaar, K.; van der Neut, J.; Ruigrok, E.; Draganov, D.; Hunziker, J.; Slob, E.; Thorbecke, J.; Snieder, R.

2008-12-01

It is well-known that under specific conditions the crosscorrelation of wavefields observed at two receivers yields the impulse response between these receivers. This principle is known as 'Green's function retrieval' or 'seismic interferometry'. Recently it has been recognized that in many situations it can be advantageous to replace the correlation process by deconvolution. One of the advantages is that deconvolution compensates for the waveform emitted by the source; another advantage is that it is not necessary to assume that the medium is lossless. The approaches that have been developed to date employ a 1D deconvolution process. We propose a method for seismic interferometry by multidimensional deconvolution and show that under specific circumstances the method compensates for irregularities in the source distribution. This is an important difference with crosscorrelation methods, which rely on the condition that waves are equipartitioned. This condition is for example fulfilled when the sources are regularly distributed along a closed surface and the power spectra of the sources are identical. The proposed multidimensional deconvolution method compensates for anisotropic illumination, without requiring knowledge about the positions and the spectra of the sources.

Multidimensional poverty and catastrophic health spending in the mountainous regions of Myanmar, Nepal and India.

PubMed

Mohanty, Sanjay K; Agrawal, Nand Kishor; Mahapatra, Bidhubhusan; Choudhury, Dhrupad; Tuladhar, Sabarnee; Holmgren, E Valdemar

2017-01-18

Economic burden to households due to out-of-pocket expenditure (OOPE) is large in many Asian countries. Though studies suggest increasing household poverty due to high OOPE in developing countries, studies on association of multidimensional poverty and household health spending is limited. This paper tests the hypothesis that the multidimensionally poor are more likely to incur catastrophic health spending cutting across countries. Data from the Poverty and Vulnerability Assessment (PVA) Survey carried out by the International Center for Integrated Mountain Development (ICIMOD) has been used in the analyses. The PVA survey was a comprehensive household survey that covered the mountainous regions of India, Nepal and Myanmar. A total of 2647 households from India, 2310 households in Nepal and 4290 households in Myanmar covered under the PVA survey. Poverty is measured in a multidimensional framework by including the dimensions of education, income and energy, water and sanitation using the Alkire and Foster method. Health shock is measured using the frequency of illness, family sickness and death of any family member in a reference period of one year. Catastrophic health expenditure is defined as 40% above the household's capacity to pay. Results suggest that about three-fifths of the population in Myanmar, two-fifths of the population in Nepal and one-third of the population in India are multidimensionally poor. About 47% of the multidimensionally poor in India had incurred catastrophic health spending compared to 35% of the multidimensionally non-poor and the pattern was similar in both Nepal and Myanmar. The odds of incurring catastrophic health spending was 56% more among the multidimensionally poor than among the multidimensionally non-poor [95% CI: 1.35-1.76]. While health shocks to households are consistently significant predictors of catastrophic health spending cutting across country of residence, the educational attainment of the head of the household is not significant. The multidimensionally poor in the poorer regions are more likely to face health shocks and are less likely to afford professional health services. Increasing government spending on health and increasing households' access to health insurance can reduce catastrophic health spending and multidimensional poverty.

Screening of a Brassica napus bacterial artificial chromosome library using highly parallel single nucleotide polymorphism assays

PubMed Central

2013-01-01

Background Efficient screening of bacterial artificial chromosome (BAC) libraries with polymerase chain reaction (PCR)-based markers is feasible provided that a multidimensional pooling strategy is implemented. Single nucleotide polymorphisms (SNPs) can be screened in multiplexed format, therefore this marker type lends itself particularly well for medium- to high-throughput applications. Combining the power of multiplex-PCR assays with a multidimensional pooling system may prove to be especially challenging in a polyploid genome. In polyploid genomes two classes of SNPs need to be distinguished, polymorphisms between accessions (intragenomic SNPs) and those differentiating between homoeologous genomes (intergenomic SNPs). We have assessed whether the highly parallel Illumina GoldenGate® Genotyping Assay is suitable for the screening of a BAC library of the polyploid Brassica napus genome. Results A multidimensional screening platform was developed for a Brassica napus BAC library which is composed of almost 83,000 clones. Intragenomic and intergenomic SNPs were included in Illumina’s GoldenGate® Genotyping Assay and both SNP classes were used successfully for screening of the multidimensional BAC pools of the Brassica napus library. An optimized scoring method is proposed which is especially valuable for SNP calling of intergenomic SNPs. Validation of the genotyping results by independent methods revealed a success of approximately 80% for the multiplex PCR-based screening regardless of whether intra- or intergenomic SNPs were evaluated. Conclusions Illumina’s GoldenGate® Genotyping Assay can be efficiently used for screening of multidimensional Brassica napus BAC pools. SNP calling was specifically tailored for the evaluation of BAC pool screening data. The developed scoring method can be implemented independently of plant reference samples. It is demonstrated that intergenomic SNPs represent a powerful tool for BAC library screening of a polyploid genome. PMID:24010766

2-3D nonlocal transport model in magnetized laser plasmas.

NASA Astrophysics Data System (ADS)

Nicolaï, Philippe; Feugeas, Jean-Luc; Schurtz, Guy

2004-11-01

We present a model of nonlocal transport for multidimensional radiation magneto-hydrodynamics codes. This model, based on simplified Fokker-Planck equations, aims at extending the formulae of G Schurtz,Ph.Nicolaï and M. Busquet [Phys. Plasmas,7,4238 (2000)] to magnetized plasmas.The improvements concern various points as the electric field effects on nonlocal transport or conversely the kinetic effects on E field. However the main purpose of this work is to generalize the previous model by including magnetic field effects. A complete system of nonlocal equations is derived from kinetic equations with self-consistent E and B fields. These equations are analyzed and simplified in order to be implemented into large laser fusion codes and coupled to other relevent physics. Finally, our model allows to obtain the deformation of the electron distribution function due to nonlocal effects. This deformation leads to a non-maxwellian function which could be used to compute the influence on other physical processes.

A Multi-Dimensional Approach to Gradient Change in Phonological Acquisition: A Case Study of Disordered Speech Development

ERIC Educational Resources Information Center

Glaspey, Amy M.; MacLeod, Andrea A. N.

2010-01-01

The purpose of the current study is to document phonological change from a multidimensional perspective for a 3-year-old boy with phonological disorder by comparing three measures: (1) accuracy of consonant productions, (2) dynamic assessment, and (3) acoustic analysis. The methods included collecting a sample of the targets /s, [image omitted],…

The Synthesis Map Is a Multidimensional Educational Tool That Provides Insight into Students' Mental Models and Promotes Students' Synthetic Knowledge Generation

ERIC Educational Resources Information Center

Ortega, Ryan A.; Brame, Cynthia J.

2015-01-01

Concept mapping was developed as a method of displaying and organizing hierarchical knowledge structures. Using the new, multidimensional presentation software Prezi, we have developed a new teaching technique designed to engage higher-level skills in the cognitive domain. This tool, synthesis mapping, is a natural evolution of concept mapping,…

DEVELOPMENT AND PSYCHOMETRIC TESTING OF A MULTIDIMENSIONAL INSTRUMENT OF PERCEIVED DISCRIMINATION AMONG AFRICAN AMERICANS IN THE JACKSON HEART STUDY

PubMed Central

Sims, Mario; Wyatt, Sharon B.; Gutierrez, Mary Lou; Taylor, Herman A.; Williams, David R.

2009-01-01

Objective Assessing the discrimination-health disparities hypothesis requires psychometrically sound, multidimensional measures of discrimination. Among the available discrimination measures, few are multidimensional and none have adequate psychometric testing in a large, African American sample. We report the development and psychometric testing of the multidimensional Jackson Heart Study Discrimination (JHSDIS) Instrument. Methods A multidimensional measure assessing the occurrence, frequency, attribution, and coping responses to perceived everyday and lifetime discrimination; lifetime burden of discrimination; and effect of skin color was developed and tested in the 5302-member cohort of the Jackson Heart Study. Internal consistency was calculated by using Cronbach α. coefficient. Confirmatory factor analysis established the dimensions, and intercorrelation coefficients assessed the discriminant validity of the instrument. Setting Tri-county area of the Jackson, MS metropolitan statistical area. Results The JHSDIS was psychometrically sound (overall α=.78, .84 and .77, respectively, for the everyday and lifetime subscales). Confirmatory factor analysis yielded 11 factors, which confirmed the a priori dimensions represented. Conclusions The JHSDIS combined three scales into a single multidimensional instrument with good psychometric properties in a large sample of African Americans. This analysis lays the foundation for using this instrument in research that will examine the association between perceived discrimination and CVD among African Americans. PMID:19341164

The multidimensional perturbation value: a single metric to measure similarity and activity of treatments in high-throughput multidimensional screens.

PubMed

Hutz, Janna E; Nelson, Thomas; Wu, Hua; McAllister, Gregory; Moutsatsos, Ioannis; Jaeger, Savina A; Bandyopadhyay, Somnath; Nigsch, Florian; Cornett, Ben; Jenkins, Jeremy L; Selinger, Douglas W

2013-04-01

Screens using high-throughput, information-rich technologies such as microarrays, high-content screening (HCS), and next-generation sequencing (NGS) have become increasingly widespread. Compared with single-readout assays, these methods produce a more comprehensive picture of the effects of screened treatments. However, interpreting such multidimensional readouts is challenging. Univariate statistics such as t-tests and Z-factors cannot easily be applied to multidimensional profiles, leaving no obvious way to answer common screening questions such as "Is treatment X active in this assay?" and "Is treatment X different from (or equivalent to) treatment Y?" We have developed a simple, straightforward metric, the multidimensional perturbation value (mp-value), which can be used to answer these questions. Here, we demonstrate application of the mp-value to three data sets: a multiplexed gene expression screen of compounds and genomic reagents, a microarray-based gene expression screen of compounds, and an HCS compound screen. In all data sets, active treatments were successfully identified using the mp-value, and simulations and follow-up analyses supported the mp-value's statistical and biological validity. We believe the mp-value represents a promising way to simplify the analysis of multidimensional data while taking full advantage of its richness.

Approximate series solution of multi-dimensional, time fractional-order (heat-like) diffusion equations using FRDTM.

PubMed

Singh, Brajesh K; Srivastava, Vineet K

2015-04-01

The main goal of this paper is to present a new approximate series solution of the multi-dimensional (heat-like) diffusion equation with time-fractional derivative in Caputo form using a semi-analytical approach: fractional-order reduced differential transform method (FRDTM). The efficiency of FRDTM is confirmed by considering four test problems of the multi-dimensional time fractional-order diffusion equation. FRDTM is a very efficient, effective and powerful mathematical tool which provides exact or very close approximate solutions for a wide range of real-world problems arising in engineering and natural sciences, modelled in terms of differential equations.

Approximate series solution of multi-dimensional, time fractional-order (heat-like) diffusion equations using FRDTM

PubMed Central

Singh, Brajesh K.; Srivastava, Vineet K.

2015-01-01

The main goal of this paper is to present a new approximate series solution of the multi-dimensional (heat-like) diffusion equation with time-fractional derivative in Caputo form using a semi-analytical approach: fractional-order reduced differential transform method (FRDTM). The efficiency of FRDTM is confirmed by considering four test problems of the multi-dimensional time fractional-order diffusion equation. FRDTM is a very efficient, effective and powerful mathematical tool which provides exact or very close approximate solutions for a wide range of real-world problems arising in engineering and natural sciences, modelled in terms of differential equations. PMID:26064639

Territories typification technique with use of statistical models

NASA Astrophysics Data System (ADS)

Galkin, V. I.; Rastegaev, A. V.; Seredin, V. V.; Andrianov, A. V.

2018-05-01

Territories typification is required for solution of many problems. The results of geological zoning received by means of various methods do not always agree. That is why the main goal of the research given is to develop a technique of obtaining a multidimensional standard classified indicator for geological zoning. In the course of the research, the probabilistic approach was used. In order to increase the reliability of geological information classification, the authors suggest using complex multidimensional probabilistic indicator P K as a criterion of the classification. The second criterion chosen is multidimensional standard classified indicator Z. These can serve as characteristics of classification in geological-engineering zoning. Above mentioned indicators P K and Z are in good correlation. Correlation coefficient values for the entire territory regardless of structural solidity equal r = 0.95 so each indicator can be used in geological-engineering zoning. The method suggested has been tested and the schematic map of zoning has been drawn.

Deterministic multidimensional nonuniform gap sampling.

PubMed

Worley, Bradley; Powers, Robert

2015-12-01

Born from empirical observations in nonuniformly sampled multidimensional NMR data relating to gaps between sampled points, the Poisson-gap sampling method has enjoyed widespread use in biomolecular NMR. While the majority of nonuniform sampling schemes are fully randomly drawn from probability densities that vary over a Nyquist grid, the Poisson-gap scheme employs constrained random deviates to minimize the gaps between sampled grid points. We describe a deterministic gap sampling method, based on the average behavior of Poisson-gap sampling, which performs comparably to its random counterpart with the additional benefit of completely deterministic behavior. We also introduce a general algorithm for multidimensional nonuniform sampling based on a gap equation, and apply it to yield a deterministic sampling scheme that combines burst-mode sampling features with those of Poisson-gap schemes. Finally, we derive a relationship between stochastic gap equations and the expectation value of their sampling probability densities. Copyright © 2015 Elsevier Inc. All rights reserved.

Multidimensional Poverty and Child Survival in India

PubMed Central

Mohanty, Sanjay K.

2011-01-01

Background Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. Objectives and Methodology Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. Results The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Conclusion Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population. PMID:22046384

Interactions across Multiple Stimulus Dimensions in Primary Auditory Cortex.

PubMed

Sloas, David C; Zhuo, Ran; Xue, Hongbo; Chambers, Anna R; Kolaczyk, Eric; Polley, Daniel B; Sen, Kamal

2016-01-01

Although sensory cortex is thought to be important for the perception of complex objects, its specific role in representing complex stimuli remains unknown. Complex objects are rich in information along multiple stimulus dimensions. The position of cortex in the sensory hierarchy suggests that cortical neurons may integrate across these dimensions to form a more gestalt representation of auditory objects. Yet, studies of cortical neurons typically explore single or few dimensions due to the difficulty of determining optimal stimuli in a high dimensional stimulus space. Evolutionary algorithms (EAs) provide a potentially powerful approach for exploring multidimensional stimulus spaces based on real-time spike feedback, but two important issues arise in their application. First, it is unclear whether it is necessary to characterize cortical responses to multidimensional stimuli or whether it suffices to characterize cortical responses to a single dimension at a time. Second, quantitative methods for analyzing complex multidimensional data from an EA are lacking. Here, we apply a statistical method for nonlinear regression, the generalized additive model (GAM), to address these issues. The GAM quantitatively describes the dependence between neural response and all stimulus dimensions. We find that auditory cortical neurons in mice are sensitive to interactions across dimensions. These interactions are diverse across the population, indicating significant integration across stimulus dimensions in auditory cortex. This result strongly motivates using multidimensional stimuli in auditory cortex. Together, the EA and the GAM provide a novel quantitative paradigm for investigating neural coding of complex multidimensional stimuli in auditory and other sensory cortices.

Visual modeling in an analysis of multidimensional data

NASA Astrophysics Data System (ADS)

Zakharova, A. A.; Vekhter, E. V.; Shklyar, A. V.; Pak, A. J.

2018-01-01

The article proposes an approach to solve visualization problems and the subsequent analysis of multidimensional data. Requirements to the properties of visual models, which were created to solve analysis problems, are described. As a perspective direction for the development of visual analysis tools for multidimensional and voluminous data, there was suggested an active use of factors of subjective perception and dynamic visualization. Practical results of solving the problem of multidimensional data analysis are shown using the example of a visual model of empirical data on the current state of studying processes of obtaining silicon carbide by an electric arc method. There are several results of solving this problem. At first, an idea of possibilities of determining the strategy for the development of the domain, secondly, the reliability of the published data on this subject, and changes in the areas of attention of researchers over time.

Effectiveness of Multidimensional Cancer Survivor Rehabilitation and Cost-Effectiveness of Cancer Rehabilitation in General: A Systematic Review

PubMed Central

Mewes, Janne C.; IJzerman, Maarten J.; van Harten, Wim H.

2012-01-01

Introduction. Many cancer survivors suffer from a combination of disease- and treatment-related morbidities and complaints after primary treatment. There is a growing evidence base for the effectiveness of monodimensional rehabilitation interventions; in practice, however, patients often participate in multidimensional programs. This study systematically reviews evidence regarding effectiveness of multidimensional rehabilitation programs for cancer survivors and cost-effectiveness of cancer rehabilitation in general. Methods. The published literature was systematically reviewed. Data were extracted using standardized forms and were summarized narratively. Results. Sixteen effectiveness and six cost-effectiveness studies were included. Multidimensional rehabilitation programs were found to be effective, but not more effective than monodimensional interventions, and not on all outcome measures. Effect sizes for quality of life were in the range of −0.12 (95% confidence interval [CI], −0.45–0.20) to 0.98 (95% CI, 0.69–1.29). Incremental cost-effectiveness ratios ranged from −€16,976, indicating cost savings, to €11,057 per quality-adjusted life year. Conclusions. The evidence for multidimensional interventions and the economic impact of rehabilitation studies is scarce and dominated by breast cancer studies. Studies published so far report statistically significant benefits for multidimensional interventions over usual care, most notably for the outcomes fatigue and physical functioning. An additional benefit of multidimensional over monodimensional rehabilitation was not found, but this was also sparsely reported on. Available economic evaluations assessed very different rehabilitation interventions. Yet, despite low comparability, all showed favorable cost-effectiveness ratios. Future studies should focus their designs on the comparative effectiveness and cost-effectiveness of multidimensional programs. PMID:22982580

A study of hydriding kinetics of metal hydrides using a physically based model

NASA Astrophysics Data System (ADS)

Voskuilen, Tyler G.

The reaction of hydrogen with metals to form metal hydrides has numerous potential energy storage and management applications. The metal hydrogen system has a high volumetric energy density and is often reversible with a high cycle life. The stored hydrogen can be used to produce energy through combustion, reaction in a fuel cell, or electrochemically in metal hydride batteries. The high enthalpy of the metal-hydrogen reaction can also be used for rapid heat removal or delivery. However, improving the often poor gravimetric performance of such systems through the use of lightweight metals usually comes at the cost of reduced reaction rates or the requirement of pressure and temperature conditions far from the desired operating conditions. In this work, a 700 bar Sievert system was developed at the Purdue Hydrogen Systems Laboratory to study the kinetic and thermodynamic behavior of high pressure hydrogen absorption under near-ambient temperatures. This system was used to determine the kinetic and thermodynamic properties of TiCrMn, an intermetallic metal hydride of interest due to its ambient temperature performance for vehicular applications. A commonly studied intermetallic hydride, LaNi5, was also characterized as a base case for the phase field model. The analysis of the data obtained from such a system necessitate the use of specialized techniques to decouple the measured reaction rates from experimental conditions. These techniques were also developed as a part of this work. Finally, a phase field model of metal hydride formation in mass-transport limited interstitial solute reactions based on the regular solution model was developed and compared with measured kinetics of LaNi5 and TiCrMn. This model aided in the identification of key reaction features and was used to verify the proposed technique for the analysis of gas-solid reaction rates determined volumetrically. Additionally, the phase field model provided detailed quantitative predictions of the effects of multidimensional phase growth and transitions between rate-limiting processes on the experimentally determined reaction rates. Unlike conventional solid state reaction analysis methods, this model relies fully on rate parameters based on the physical mechanisms occurring in the hydride reaction and can be extended to reactions in any dimension.

Capillary trap column with strong cation-exchange monolith for automated shotgun proteome analysis.

PubMed

Wang, Fangjun; Dong, Jing; Jiang, Xiaogang; Ye, Mingliang; Zou, Hanfa

2007-09-01

A 150 microm internal diameter capillary monolithic column with a strong cation-exchange stationary phase was prepared by direct in situ polymerization of ethylene glycol methacrylate phosphate and bisacrylamide in a trinary porogenic solvent consisting dimethylsulfoxide, dodecanol, and N,N'-dimethylformamide. This phosphate monolithic column exhibits higher dynamic binding capacity, faster kinetic adsorption of peptides, and more than 10 times higher permeability than the column packed with commercially available strong cation-exchange particles. It was applied as a trap column in a nanoflow liquid chromatography-tandem mass spectrometry system for automated sample injection and online multidimensional separation. It was observed that the sample could be loaded at a flow rate as high as 40 microL/min with a back pressure of approximately 1300 psi and without compromising the separation efficiency. Because of its good orthogonality to the reversed phase separation mechanism, the phosphate monolithic trap column was coupled with a reversed-phase column for online multidimensional separation of 19 microg of the tryptic digest of yeast proteins. A total of 1522 distinct proteins were identified from 5608 unique peptides (total of 54,780 peptides) at the false positive rate only 0.46%.

Affiliation with Delinquent Peers as a Mediator of the Effects of Multidimensional Treatment Foster Care for Delinquent Girls

ERIC Educational Resources Information Center

Van Ryzin, Mark J.; Leve, Leslie D.

2012-01-01

Objective: This study evaluated the ability of delinquent peer affiliation to mediate the effects of multidimensional treatment foster care (MTFC; Chamberlain, 2003) on girls' delinquent behavior. Method: This study used a sample of girls from 2 cohorts (N = 166; M = 15.31 years old at baseline, range 13-17 years; 74% European American, 2% African…

Kinetic Modeling of Slow Energy Release in Non-Ideal Carbon Rich Explosives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vitello, P; Fried, L; Glaesemann, K

2006-06-20

We present here the first self-consistent kinetic based model for long time-scale energy release in detonation waves in the non-ideal explosive LX-17. Non-ideal, insensitive carbon rich explosives, such as those based on TATB, are believed to have significant late-time slow release in energy. One proposed source of this energy is diffusion-limited growth of carbon clusters. In this paper we consider the late-time energy release problem in detonation waves using the thermochemical code CHEETAH linked to a multidimensional ALE hydrodynamics model. The linked CHEETAH-ALE model dimensional treats slowly reacting chemical species using kinetic rate laws, with chemical equilibrium assumed for speciesmore » coupled via fast time-scale reactions. In the model presented here we include separate rate equations for the transformation of the un-reacted explosive to product gases and for the growth of a small particulate form of condensed graphite to a large particulate form. The small particulate graphite is assumed to be in chemical equilibrium with the gaseous species allowing for coupling between the instantaneous thermodynamic state and the production of graphite clusters. For the explosive burn rate a pressure dependent rate law was used. Low pressure freezing of the gas species mass fractions was also included to account for regions where the kinetic coupling rates become longer than the hydrodynamic time-scales. The model rate parameters were calibrated using cylinder and rate-stick experimental data. Excellent long time agreement and size effect results were achieved.« less

From analytical solutions of solute transport equations to multidimensional time-domain random walk (TDRW) algorithms

NASA Astrophysics Data System (ADS)

Bodin, Jacques

2015-03-01

In this study, new multi-dimensional time-domain random walk (TDRW) algorithms are derived from approximate one-dimensional (1-D), two-dimensional (2-D), and three-dimensional (3-D) analytical solutions of the advection-dispersion equation and from exact 1-D, 2-D, and 3-D analytical solutions of the pure-diffusion equation. These algorithms enable the calculation of both the time required for a particle to travel a specified distance in a homogeneous medium and the mass recovery at the observation point, which may be incomplete due to 2-D or 3-D transverse dispersion or diffusion. The method is extended to heterogeneous media, represented as a piecewise collection of homogeneous media. The particle motion is then decomposed along a series of intermediate checkpoints located on the medium interface boundaries. The accuracy of the multi-dimensional TDRW method is verified against (i) exact analytical solutions of solute transport in homogeneous media and (ii) finite-difference simulations in a synthetic 2-D heterogeneous medium of simple geometry. The results demonstrate that the method is ideally suited to purely diffusive transport and to advection-dispersion transport problems dominated by advection. Conversely, the method is not recommended for highly dispersive transport problems because the accuracy of the advection-dispersion TDRW algorithms degrades rapidly for a low Péclet number, consistent with the accuracy limit of the approximate analytical solutions. The proposed approach provides a unified methodology for deriving multi-dimensional time-domain particle equations and may be applicable to other mathematical transport models, provided that appropriate analytical solutions are available.

Parsimony and goodness-of-fit in multi-dimensional NMR inversion

NASA Astrophysics Data System (ADS)

Babak, Petro; Kryuchkov, Sergey; Kantzas, Apostolos

2017-01-01

Multi-dimensional nuclear magnetic resonance (NMR) experiments are often used for study of molecular structure and dynamics of matter in core analysis and reservoir evaluation. Industrial applications of multi-dimensional NMR involve a high-dimensional measurement dataset with complicated correlation structure and require rapid and stable inversion algorithms from the time domain to the relaxation rate and/or diffusion domains. In practice, applying existing inverse algorithms with a large number of parameter values leads to an infinite number of solutions with a reasonable fit to the NMR data. The interpretation of such variability of multiple solutions and selection of the most appropriate solution could be a very complex problem. In most cases the characteristics of materials have sparse signatures, and investigators would like to distinguish the most significant relaxation and diffusion values of the materials. To produce an easy to interpret and unique NMR distribution with the finite number of the principal parameter values, we introduce a new method for NMR inversion. The method is constructed based on the trade-off between the conventional goodness-of-fit approach to multivariate data and the principle of parsimony guaranteeing inversion with the least number of parameter values. We suggest performing the inversion of NMR data using the forward stepwise regression selection algorithm. To account for the trade-off between goodness-of-fit and parsimony, the objective function is selected based on Akaike Information Criterion (AIC). The performance of the developed multi-dimensional NMR inversion method and its comparison with conventional methods are illustrated using real data for samples with bitumen, water and clay.

A Review of Multidimensional, Multifluid Intermediate-scale Experiments: Flow Behavior, Saturation Imaging, and Tracer Detection and Quantification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oostrom, Mart; Dane, J. H.; Wietsma, Thomas W.

2007-08-01

A review is presented of original multidimensional, intermediate-scale experiments involving non-aqueous phase liquid (NAPL) flow behavior, imaging, and detection/quantification with solute tracers. In a companion paper (Oostrom, M., J.H. Dane, and T.W. Wietsma. 2006. A review of multidimensional, multifluid intermediate-scale experiments: Nonaqueous phase dissolution and enhanced remediation. Vadose Zone Journal 5:570-598) experiments related to aqueous dissolution and enhanced remediation were discussed. The experiments investigating flow behavior include infiltration and redistribution experiments with both light and dense NAPLs in homogeneous and heterogeneous porous medium systems. The techniques used for NAPL saturation mapping for intermediate-scale experiments include photon-attenuation methods such as gammamore » and X-ray techniques, and photographic methods such as the light reflection, light transmission, and multispectral image analysis techniques. Solute tracer methods used for detection and quantification of NAPL in the subsurface are primarily limited to variations of techniques comparing the behavior of conservative and partitioning tracers. Besides a discussion of the experimental efforts, recommendations for future research at this laboratory scale are provided.« less

Monte Carlo methods for multidimensional integration for European option pricing

NASA Astrophysics Data System (ADS)

Todorov, V.; Dimov, I. T.

2016-10-01

In this paper, we illustrate examples of highly accurate Monte Carlo and quasi-Monte Carlo methods for multiple integrals related to the evaluation of European style options. The idea is that the value of the option is formulated in terms of the expectation of some random variable; then the average of independent samples of this random variable is used to estimate the value of the option. First we obtain an integral representation for the value of the option using the risk neutral valuation formula. Then with an appropriations change of the constants we obtain a multidimensional integral over the unit hypercube of the corresponding dimensionality. Then we compare a specific type of lattice rules over one of the best low discrepancy sequence of Sobol for numerical integration. Quasi-Monte Carlo methods are compared with Adaptive and Crude Monte Carlo techniques for solving the problem. The four approaches are completely different thus it is a question of interest to know which one of them outperforms the other for evaluation multidimensional integrals in finance. Some of the advantages and disadvantages of the developed algorithms are discussed.

Influence of Multidimensionality on Convergence of Sampling in Protein Simulation

NASA Astrophysics Data System (ADS)

Metsugi, Shoichi

2005-06-01

We study the problem of convergence of sampling in protein simulation originating in the multidimensionality of protein’s conformational space. Since several important physical quantities are given by second moments of dynamical variables, we attempt to obtain the time of simulation necessary for their sufficient convergence. We perform a molecular dynamics simulation of a protein and the subsequent principal component (PC) analysis as a function of simulation time T. As T increases, PC vectors with smaller amplitude of variations are identified and their amplitudes are equilibrated before identifying and equilibrating vectors with larger amplitude of variations. This sequential identification and equilibration mechanism makes protein simulation a useful method although it has an intrinsic multidimensional nature.

Critical evaluation of Jet-A spray combustion using propane chemical kinetics in gas turbine combustion simulated by KIVA-2

NASA Technical Reports Server (NTRS)

Nguyen, H. L.; Ying, S.-J.

1990-01-01

Jet-A spray combustion has been evaluated in gas turbine combustion with the use of propane chemical kinetics as the first approximation for the chemical reactions. Here, the numerical solutions are obtained by using the KIVA-2 computer code. The KIVA-2 code is the most developed of the available multidimensional combustion computer programs for application of the in-cylinder combustion dynamics of internal combustion engines. The released version of KIVA-2 assumes that 12 chemical species are present; the code uses an Arrhenius kinetic-controlled combustion model governed by a four-step global chemical reaction and six equilibrium reactions. Researchers efforts involve the addition of Jet-A thermophysical properties and the implementation of detailed reaction mechanisms for propane oxidation. Three different detailed reaction mechanism models are considered. The first model consists of 131 reactions and 45 species. This is considered as the full mechanism which is developed through the study of chemical kinetics of propane combustion in an enclosed chamber. The full mechanism is evaluated by comparing calculated ignition delay times with available shock tube data. However, these detailed reactions occupy too much computer memory and CPU time for the computation. Therefore, it only serves as a benchmark case by which to evaluate other simplified models. Two possible simplified models were tested in the existing computer code KIVA-2 for the same conditions as used with the full mechanism. One model is obtained through a sensitivity analysis using LSENS, the general kinetics and sensitivity analysis program code of D. A. Bittker and K. Radhakrishnan. This model consists of 45 chemical reactions and 27 species. The other model is based on the work published by C. K. Westbrook and F. L. Dryer.

Efficient implementation of multidimensional fast fourier transform on a distributed-memory parallel multi-node computer

DOEpatents

Bhanot, Gyan V [Princeton, NJ; Chen, Dong [Croton-On-Hudson, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

2012-01-10

The present in invention is directed to a method, system and program storage device for efficiently implementing a multidimensional Fast Fourier Transform (FFT) of a multidimensional array comprising a plurality of elements initially distributed in a multi-node computer system comprising a plurality of nodes in communication over a network, comprising: distributing the plurality of elements of the array in a first dimension across the plurality of nodes of the computer system over the network to facilitate a first one-dimensional FFT; performing the first one-dimensional FFT on the elements of the array distributed at each node in the first dimension; re-distributing the one-dimensional FFT-transformed elements at each node in a second dimension via "all-to-all" distribution in random order across other nodes of the computer system over the network; and performing a second one-dimensional FFT on elements of the array re-distributed at each node in the second dimension, wherein the random order facilitates efficient utilization of the network thereby efficiently implementing the multidimensional FFT. The "all-to-all" re-distribution of array elements is further efficiently implemented in applications other than the multidimensional FFT on the distributed-memory parallel supercomputer.

Efficient implementation of a multidimensional fast fourier transform on a distributed-memory parallel multi-node computer

DOEpatents

Bhanot, Gyan V [Princeton, NJ; Chen, Dong [Croton-On-Hudson, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

2008-01-01

The present in invention is directed to a method, system and program storage device for efficiently implementing a multidimensional Fast Fourier Transform (FFT) of a multidimensional array comprising a plurality of elements initially distributed in a multi-node computer system comprising a plurality of nodes in communication over a network, comprising: distributing the plurality of elements of the array in a first dimension across the plurality of nodes of the computer system over the network to facilitate a first one-dimensional FFT; performing the first one-dimensional FFT on the elements of the array distributed at each node in the first dimension; re-distributing the one-dimensional FFT-transformed elements at each node in a second dimension via "all-to-all" distribution in random order across other nodes of the computer system over the network; and performing a second one-dimensional FFT on elements of the array re-distributed at each node in the second dimension, wherein the random order facilitates efficient utilization of the network thereby efficiently implementing the multidimensional FFT. The "all-to-all" re-distribution of array elements is further efficiently implemented in applications other than the multidimensional FFT on the distributed-memory parallel supercomputer.

Application of the method of steepest descent to laminated shield weight optimization with several constraints: Theory

NASA Technical Reports Server (NTRS)

Lahti, G. P.

1971-01-01

The method of steepest descent used in optimizing one-dimensional layered radiation shields is extended to multidimensional, multiconstraint situations. The multidimensional optimization algorithm and equations are developed for the case of a dose constraint in any one direction being dependent only on the shield thicknesses in that direction and independent of shield thicknesses in other directions. Expressions are derived for one-, two-, and three-dimensional cases (one, two, and three constraints). The precedure is applicable to the optimization of shields where there are different dose constraints and layering arrangements in the principal directions.

A New Computational Method to Fit the Weighted Euclidean Distance Model.

ERIC Educational Resources Information Center

De Leeuw, Jan; Pruzansky, Sandra

1978-01-01

A computational method for weighted euclidean distance scaling (a method of multidimensional scaling) which combines aspects of an "analytic" solution with an approach using loss functions is presented. (Author/JKS)

A comparative study of Conroy and Monte Carlo methods applied to multiple quadratures and multiple scattering

NASA Technical Reports Server (NTRS)

Deepak, A.; Fluellen, A.

1978-01-01

An efficient numerical method of multiple quadratures, the Conroy method, is applied to the problem of computing multiple scattering contributions in the radiative transfer through realistic planetary atmospheres. A brief error analysis of the method is given and comparisons are drawn with the more familiar Monte Carlo method. Both methods are stochastic problem-solving models of a physical or mathematical process and utilize the sampling scheme for points distributed over a definite region. In the Monte Carlo scheme the sample points are distributed randomly over the integration region. In the Conroy method, the sample points are distributed systematically, such that the point distribution forms a unique, closed, symmetrical pattern which effectively fills the region of the multidimensional integration. The methods are illustrated by two simple examples: one, of multidimensional integration involving two independent variables, and the other, of computing the second order scattering contribution to the sky radiance.

Multi-dimensional construction of a novel active yolk@conductive shell nanofiber web as a self-standing anode for high-performance lithium-ion batteries

NASA Astrophysics Data System (ADS)

Liu, Hao; Chen, Luyi; Liang, Yeru; Fu, Ruowen; Wu, Dingcai

2015-11-01

A novel active yolk@conductive shell nanofiber web with a unique synergistic advantage of various hierarchical nanodimensional objects including the 0D monodisperse SiO2 yolks, the 1D continuous carbon shell and the 3D interconnected non-woven fabric web has been developed by an innovative multi-dimensional construction method, and thus demonstrates excellent electrochemical properties as a self-standing LIB anode.A novel active yolk@conductive shell nanofiber web with a unique synergistic advantage of various hierarchical nanodimensional objects including the 0D monodisperse SiO2 yolks, the 1D continuous carbon shell and the 3D interconnected non-woven fabric web has been developed by an innovative multi-dimensional construction method, and thus demonstrates excellent electrochemical properties as a self-standing LIB anode. Electronic supplementary information (ESI) available: Experimental details and additional information about material characterization. See DOI: 10.1039/c5nr06531c

High-frequency stock linkage and multi-dimensional stationary processes

NASA Astrophysics Data System (ADS)

Wang, Xi; Bao, Si; Chen, Jingchao

2017-02-01

In recent years, China's stock market has experienced dramatic fluctuations; in particular, in the second half of 2014 and 2015, the market rose sharply and fell quickly. Many classical financial phenomena, such as stock plate linkage, appeared repeatedly during this period. In general, these phenomena have usually been studied using daily-level data or minute-level data. Our paper focuses on the linkage phenomenon in Chinese stock 5-second-level data during this extremely volatile period. The method used to select the linkage points and the arbitrage strategy are both based on multi-dimensional stationary processes. A new program method for testing the multi-dimensional stationary process is proposed in our paper, and the detailed program is presented in the paper's appendix. Because of the existence of the stationary process, the strategy's logarithmic cumulative average return will converge under the condition of the strong ergodic theorem, and this ensures the effectiveness of the stocks' linkage points and the more stable statistical arbitrage strategy.

A model for the nonlocal transport and the associated distribution function deformation in magnetized laser-plasmas

NASA Astrophysics Data System (ADS)

Nicolaï, Ph.; Feugeas, J.-L.; Schurtz, G.

2006-06-01

We present a model of nonlocal transport for multidimensional radiation magneto hydrodynamic codes. In laser produced plasmas, it is now believed that the heat transfert can be strongly modified by the nonlocal nature of the electron conduction. Nevertheless other mechanisms as self generated magnetic fields may affect heat transport too. The model described in this work aims at extending the formula of G. Schurtz, Ph. Nicolaï and M. Busquet [1] to magnetized plasmas. A system of nonlocal equations is derived from kinetic equations with self-consistent electric and magnetic fields. These equations are analyzed and applied to a physical problem in order to demonstrate the main features of the model.

Atmospheric studies related to aerospace activities and remote sensing technology

NASA Technical Reports Server (NTRS)

Sze, N. D.; Isaacs, R. G.; Ko, M.; Mcelroy, M. B.

1981-01-01

Parallel investigations were conducted relating to: the sensitivity of 1-D photochemical model simulated column ozone perturbations due to a projected fleet of 1000 aircraft cruising 7 hours per day at altitudes of 15-16 and 18-19 km to uncertainties in kinetic rate constant data determining modeled OH concentrations and eddy diffusivity profile parameterization and a comparison of the inherent strengths and weaknesses of Eulerian and Langrangian averaging processes in the development of multidimensional models and investigation of approaches to applying the Generalized Lagrangian Mean (GLM) formalism to zonal-mean models. The role of multiple scattering and Earth curvature in the evaluation of diurnally dependent photodissociation rates and trace species variations was examined.

Final Report: SciDAC Computational Astrophysics Consortium (at Princeton University)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burrows, Adam

Supernova explosions are the central events in astrophysics. They are the major agencies of change in the interstellar medium, driving star formation and the evolution of galaxies. Their gas remnants are the birthplaces of the cosmic rays. Such is their brightness that they can be used as standard candles to measure the size and geometry of the universe and their investigation draws on particle and nuclear physics, radiative transfer, kinetic theory, gravitational physics, thermodynamics, and the numerical arts. Hence, supernovae are unrivaled astrophysical laboratories. We will develop new state-of-the-art multi-dimensional radiation hydrodynamic codes to address this and other related astrophysicalmore » phenomena.« less

Discrete models for the numerical analysis of time-dependent multidimensional gas dynamics

NASA Technical Reports Server (NTRS)

Roe, P. L.

1984-01-01

A possible technique is explored for extending to multidimensional flows some of the upwind-differencing methods that are highly successful in the one-dimensional case. Emphasis is on the two-dimensional case, and the flow domain is assumed to be divided into polygonal computational elements. Inside each element, the flow is represented by a local superposition of elementary solutions consisting of plane waves not necessarily aligned with the element boundaries.

Chapter 3. A multidimensional model for narrative analysis of substance use-related dependency.

PubMed

Larsson, Sam; von Braun, Therese; Lilja, John

2013-11-01

This chapter examines the possibilities and limitations of using a narrative method as a framework within a multidimensional model for exploring and analyzing the use and misuse of alcohol and drugs. It is posited that a multidimensional model, based on narrative reasoning, can give a more detailed and specific understanding of substance users, who represent a heterogeneous population of people, and of substance use-related dependency problems. Such a model describes and analyses the drug-use related problems in a manner that provides holistic and important information and knowledge about the person by contextual and situation interaction processes which are involved in the use/misuse of alcohol and drugs. Tentative conclusions and unresolved critical issues are considered.

Fuzzy Regression Prediction and Application Based on Multi-Dimensional Factors of Freight Volume

NASA Astrophysics Data System (ADS)

Xiao, Mengting; Li, Cheng

2018-01-01

Based on the reality of the development of air cargo, the multi-dimensional fuzzy regression method is used to determine the influencing factors, and the three most important influencing factors of GDP, total fixed assets investment and regular flight route mileage are determined. The system’s viewpoints and analogy methods, the use of fuzzy numbers and multiple regression methods to predict the civil aviation cargo volume. In comparison with the 13th Five-Year Plan for China’s Civil Aviation Development (2016-2020), it is proved that this method can effectively improve the accuracy of forecasting and reduce the risk of forecasting. It is proved that this model predicts civil aviation freight volume of the feasibility, has a high practical significance and practical operation.

The PedsQL in pediatric cancer: reliability and validity of the Pediatric Quality of Life Inventory Generic Core Scales, Multidimensional Fatigue Scale, and Cancer Module.

PubMed

Varni, James W; Burwinkle, Tasha M; Katz, Ernest R; Meeske, Kathy; Dickinson, Paige

2002-04-01

The Pediatric Quality of Life Inventory (PedsQL) is a modular instrument designed to measure health-related quality of life (HRQOL) in children and adolescents ages 2-18 years. The PedsQL 4.0 Generic Core Scales are multidimensional child self-report and parent proxy-report scales developed as the generic core measure to be integrated with the PedsQL disease specific modules. The PedsQL Multidimensional Fatigue Scale was designed to measure fatigue in pediatric patients. The PedsQL 3.0 Cancer Module was designed to measure pediatric cancer specific HRQOL. The PedsQL Generic Core Scales, Multidimensional Fatigue Scale, and Cancer Module were administered to 339 families (220 child self-reports; 337 parent proxy-reports). Internal consistency reliability for the PedsQL Generic Core Total Scale Score (alpha = 0.88 child, 0.93 parent report), Multidimensional Fatigue Total Scale Score (alpha = 0.89 child, 0.92 parent report) and most Cancer Module Scales (average alpha = 0.72 child, 0.87 parent report) demonstrated reliability acceptable for group comparisons. Validity was demonstrated using the known-groups method. The PedsQL distinguished between healthy children and children with cancer as a group, and among children on-treatment versus off-treatment. The validity of the PedsQL Multidimensional Fatigue Scale was further demonstrated through hypothesized intercorrelations with dimensions of generic and cancer specific HRQOL. The results demonstrate the reliability and validity of the PedsQL Generic Core Scales, Multidimensional Fatigue Scale, and Cancer Module in pediatric cancer. The PedsQL may be utilized as an outcome measure in clinical trials, research, and clinical practice. Copyright 2002 American Cancer Society.

The PedsQL Multidimensional Fatigue Scale in pediatric rheumatology: reliability and validity.

PubMed

Varni, James W; Burwinkle, Tasha M; Szer, Ilona S

2004-12-01

. The PedsQL (Pediatric Quality of Life Inventory) is a modular instrument designed to measure health related quality of life (HRQOL) in children and adolescents ages 2-18 years. The recently developed 18-item PedsQL Multidimensional Fatigue Scale was designed to measure fatigue in pediatric patients and comprises the General Fatigue Scale (6 items), Sleep/Rest Fatigue Scale (6 items), and Cognitive Fatigue Scale (6 items). The PedsQL 4.0 Generic Core Scales were developed as the generic core measure to be integrated with the PedsQL Disease-Specific Modules. The PedsQL 3.0 Rheumatology Module was designed to measure pediatric rheumatology-specific HRQOL. Methods. The PedsQL Multidimensional Fatigue Scale, Generic Core Scales, and Rheumatology Module were administered to 163 children and 154 parents (183 families accrued overall) recruited from a pediatric rheumatology clinic. Results. Internal consistency reliability for the PedsQL Multidimensional Fatigue Scale Total Score (a = 0.95 child, 0.95 parent report), General Fatigue Scale (a = 0.93 child, 0.92 parent), Sleep/Rest Fatigue Scale (a = 0.88 child, 0.90 parent), and Cognitive Fatigue Scale (a = 0.93 child, 0.96 parent) were excellent for group and individual comparisons. The validity of the PedsQL Multidimensional Fatigue Scale was confirmed through hypothesized intercorrelations with dimensions of generic and rheumatology-specific HRQOL. The PedsQL Multidimensional Fatigue Scale distinguished between healthy children and children with rheumatic diseases as a group, and was associated with greater disease severity. Children with fibromyalgia manifested greater fatigue than children with other rheumatic diseases. The results confirm the initial reliability and validity of the PedsQL Multidimensional Fatigue Scale in pediatric rheumatology.

Hybrid simulations of weakly collisional plasmas

NASA Astrophysics Data System (ADS)

Xia, Qian; Reville, Brian; Tzoufras, Michail

2016-10-01

Laser produced plasma experiments can be exploited to investigate phenomena of astrophysical relevance. The high densities and velocities that can be generated in the laboratory provide ideal conditions to investigate weakly collisional or collisionless plasma shock physics. In addition, the high temperatures permit magnetic and kinetic Reynolds numbers that are difficult to achieve in other plasma experiments, opening the possibility to study plasma dynamo. Many of these experiments are based on a classic plasma physics problem, namely the interpenetration of two plasma flows. To investigate this phenomenon, we are constructing a novel multi-dimensional hybrid numerical scheme, that solves the ion distribution kinetically via a Vlasov-Fokker-Planck equation, with electrons providing a charge neutralizing fluid. This allows us to follow the evolution on hydrodynamic timescales, while permitting inclusion ofcollisionlesseffects on small scales. It also could be used to study the increasing collisional effects due to the stiff gradient and weakly anisotropic velocity distribution. We present some preliminary validation tests for the code, demonstrating its ability to accurately model key processes that are relevant to laboratory and astrophysical plasmas.

Path integral learning of multidimensional movement trajectories

NASA Astrophysics Data System (ADS)

André, João; Santos, Cristina; Costa, Lino

2013-10-01

This paper explores the use of Path Integral Methods, particularly several variants of the recent Path Integral Policy Improvement (PI2) algorithm in multidimensional movement parametrized policy learning. We rely on Dynamic Movement Primitives (DMPs) to codify discrete and rhythmic trajectories, and apply the PI2-CMA and PIBB methods in the learning of optimal policy parameters, according to different cost functions that inherently encode movement objectives. Additionally we merge both of these variants and propose the PIBB-CMA algorithm, comparing all of them with the vanilla version of PI2. From the obtained results we conclude that PIBB-CMA surpasses all other methods in terms of convergence speed and iterative final cost, which leads to an increased interest in its application to more complex robotic problems.

A two-dimensional Riemann solver with self-similar sub-structure - Alternative formulation based on least squares projection

NASA Astrophysics Data System (ADS)

Balsara, Dinshaw S.; Vides, Jeaniffer; Gurski, Katharine; Nkonga, Boniface; Dumbser, Michael; Garain, Sudip; Audit, Edouard

2016-01-01

Just as the quality of a one-dimensional approximate Riemann solver is improved by the inclusion of internal sub-structure, the quality of a multidimensional Riemann solver is also similarly improved. Such multidimensional Riemann problems arise when multiple states come together at the vertex of a mesh. The interaction of the resulting one-dimensional Riemann problems gives rise to a strongly-interacting state. We wish to endow this strongly-interacting state with physically-motivated sub-structure. The self-similar formulation of Balsara [16] proves especially useful for this purpose. While that work is based on a Galerkin projection, in this paper we present an analogous self-similar formulation that is based on a different interpretation. In the present formulation, we interpret the shock jumps at the boundary of the strongly-interacting state quite literally. The enforcement of the shock jump conditions is done with a least squares projection (Vides, Nkonga and Audit [67]). With that interpretation, we again show that the multidimensional Riemann solver can be endowed with sub-structure. However, we find that the most efficient implementation arises when we use a flux vector splitting and a least squares projection. An alternative formulation that is based on the full characteristic matrices is also presented. The multidimensional Riemann solvers that are demonstrated here use one-dimensional HLLC Riemann solvers as building blocks. Several stringent test problems drawn from hydrodynamics and MHD are presented to show that the method works. Results from structured and unstructured meshes demonstrate the versatility of our method. The reader is also invited to watch a video introduction to multidimensional Riemann solvers on http://www.nd.edu/ dbalsara/Numerical-PDE-Course.

Study of multi-dimensional radiative energy transfer in molecular gases

NASA Technical Reports Server (NTRS)

Liu, Jiwen; Tiwari, S. N.

1993-01-01

The Monte Carlo method (MCM) is applied to analyze radiative heat transfer in nongray gases. The nongray model employed is based on the statistical arrow band model with an exponential-tailed inverse intensity distribution. Consideration of spectral correlation results in some distinguishing features of the Monte Carlo formulations. Validation of the Monte Carlo formulations has been conducted by comparing results of this method with other solutions. Extension of a one-dimensional problem to a multi-dimensional problem requires some special treatments in the Monte Carlo analysis. Use of different assumptions results in different sets of Monte Carlo formulations. The nongray narrow band formulations provide the most accurate results.

Real-time monitoring and visualization of the multi-dimensional motion of an anisotropic nanoparticle

NASA Astrophysics Data System (ADS)

Go, Gi-Hyun; Heo, Seungjin; Cho, Jong-Hoi; Yoo, Yang-Seok; Kim, Minkwan; Park, Chung-Hyun; Cho, Yong-Hoon

2017-03-01

As interest in anisotropic particles has increased in various research fields, methods of tracking such particles have become increasingly desirable. Here, we present a new and intuitive method to monitor the Brownian motion of a nanowire, which can construct and visualize multi-dimensional motion of a nanowire confined in an optical trap, using a dual particle tracking system. We measured the isolated angular fluctuations and translational motion of the nanowire in the optical trap, and determined its physical properties, such as stiffness and torque constants, depending on laser power and polarization direction. This has wide implications in nanoscience and nanotechnology with levitated anisotropic nanoparticles.

Electrochemical force microscopy

DOEpatents

Kalinin, Sergei V.; Jesse, Stephen; Collins, Liam F.; Rodriguez, Brian J.

2017-01-10

A system and method for electrochemical force microscopy are provided. The system and method are based on a multidimensional detection scheme that is sensitive to forces experienced by a biased electrode in a solution. The multidimensional approach allows separation of fast processes, such as double layer charging, and charge relaxation, and slow processes, such as diffusion and faradaic reactions, as well as capturing the bias dependence of the response. The time-resolved and bias measurements can also allow probing both linear (small bias range) and non-linear (large bias range) electrochemical regimes and potentially the de-convolution of charge dynamics and diffusion processes from steric effects and electrochemical reactivity.

Using multi-dimensional Smolyak interpolation to make a sum-of-products potential

DOE Office of Scientific and Technical Information (OSTI.GOV)

Avila, Gustavo, E-mail: Gustavo-Avila@telefonica.net; Carrington, Tucker, E-mail: Tucker.Carrington@queensu.ca

2015-07-28

We propose a new method for obtaining potential energy surfaces in sum-of-products (SOP) form. If the number of terms is small enough, a SOP potential surface significantly reduces the cost of quantum dynamics calculations by obviating the need to do multidimensional integrals by quadrature. The method is based on a Smolyak interpolation technique and uses polynomial-like or spectral basis functions and 1D Lagrange-type functions. When written in terms of the basis functions from which the Lagrange-type functions are built, the Smolyak interpolant has only a modest number of terms. The ideas are tested for HONO (nitrous acid)

Real-time object recognition in multidimensional images based on joined extended structural tensor and higher-order tensor decomposition methods

NASA Astrophysics Data System (ADS)

Cyganek, Boguslaw; Smolka, Bogdan

2015-02-01

In this paper a system for real-time recognition of objects in multidimensional video signals is proposed. Object recognition is done by pattern projection into the tensor subspaces obtained from the factorization of the signal tensors representing the input signal. However, instead of taking only the intensity signal the novelty of this paper is first to build the Extended Structural Tensor representation from the intensity signal that conveys information on signal intensities, as well as on higher-order statistics of the input signals. This way the higher-order input pattern tensors are built from the training samples. Then, the tensor subspaces are built based on the Higher-Order Singular Value Decomposition of the prototype pattern tensors. Finally, recognition relies on measurements of the distance of a test pattern projected into the tensor subspaces obtained from the training tensors. Due to high-dimensionality of the input data, tensor based methods require high memory and computational resources. However, recent achievements in the technology of the multi-core microprocessors and graphic cards allows real-time operation of the multidimensional methods as is shown and analyzed in this paper based on real examples of object detection in digital images.

Multidimensional NMR inversion without Kronecker products: Multilinear inversion

NASA Astrophysics Data System (ADS)

Medellín, David; Ravi, Vivek R.; Torres-Verdín, Carlos

2016-08-01

Multidimensional NMR inversion using Kronecker products poses several challenges. First, kernel compression is only possible when the kernel matrices are separable, and in recent years, there has been an increasing interest in NMR sequences with non-separable kernels. Second, in three or more dimensions, the singular value decomposition is not unique; therefore kernel compression is not well-defined for higher dimensions. Without kernel compression, the Kronecker product yields matrices that require large amounts of memory, making the inversion intractable for personal computers. Finally, incorporating arbitrary regularization terms is not possible using the Lawson-Hanson (LH) or the Butler-Reeds-Dawson (BRD) algorithms. We develop a minimization-based inversion method that circumvents the above problems by using multilinear forms to perform multidimensional NMR inversion without using kernel compression or Kronecker products. The new method is memory efficient, requiring less than 0.1% of the memory required by the LH or BRD methods. It can also be extended to arbitrary dimensions and adapted to include non-separable kernels, linear constraints, and arbitrary regularization terms. Additionally, it is easy to implement because only a cost function and its first derivative are required to perform the inversion.

Differentially Private Synthesization of Multi-Dimensional Data using Copula Functions

PubMed Central

Li, Haoran; Xiong, Li; Jiang, Xiaoqian

2014-01-01

Differential privacy has recently emerged in private statistical data release as one of the strongest privacy guarantees. Most of the existing techniques that generate differentially private histograms or synthetic data only work well for single dimensional or low-dimensional histograms. They become problematic for high dimensional and large domain data due to increased perturbation error and computation complexity. In this paper, we propose DPCopula, a differentially private data synthesization technique using Copula functions for multi-dimensional data. The core of our method is to compute a differentially private copula function from which we can sample synthetic data. Copula functions are used to describe the dependence between multivariate random vectors and allow us to build the multivariate joint distribution using one-dimensional marginal distributions. We present two methods for estimating the parameters of the copula functions with differential privacy: maximum likelihood estimation and Kendall’s τ estimation. We present formal proofs for the privacy guarantee as well as the convergence property of our methods. Extensive experiments using both real datasets and synthetic datasets demonstrate that DPCopula generates highly accurate synthetic multi-dimensional data with significantly better utility than state-of-the-art techniques. PMID:25405241

Investigation of multidimensional control systems in the state space and wavelet medium

NASA Astrophysics Data System (ADS)

Fedosenkov, D. B.; Simikova, A. A.; Fedosenkov, B. A.

2018-05-01

The notions are introduced of “one-dimensional-point” and “multidimensional-point” automatic control systems. To demonstrate the joint use of approaches based on the concepts of state space and wavelet transforms, a method for optimal control in a state space medium represented in the form of time-frequency representations (maps), is considered. The computer-aided control system is formed on the basis of the similarity transformation method, which makes it possible to exclude the use of reduced state variable observers. 1D-material flow signals formed by primary transducers are converted by means of wavelet transformations into multidimensional concentrated-at-a point variables in the form of time-frequency distributions of Cohen’s class. The algorithm for synthesizing a stationary controller for feeding processes is given here. The conclusion is made that the formation of an optimal control law with time-frequency distributions available contributes to the improvement of transient processes quality in feeding subsystems and the mixing unit. Confirming the efficiency of the method presented is illustrated by an example of the current registration of material flows in the multi-feeding unit. The first section in your paper.

Multi-dimensional Fokker-Planck equation analysis using the modified finite element method

NASA Astrophysics Data System (ADS)

Náprstek, J.; Král, R.

2016-09-01

The Fokker-Planck equation (FPE) is a frequently used tool for the solution of cross probability density function (PDF) of a dynamic system response excited by a vector of random processes. FEM represents a very effective solution possibility, particularly when transition processes are investigated or a more detailed solution is needed. Actual papers deal with single degree of freedom (SDOF) systems only. So the respective FPE includes two independent space variables only. Stepping over this limit into MDOF systems a number of specific problems related to a true multi-dimensionality must be overcome. Unlike earlier studies, multi-dimensional simplex elements in any arbitrary dimension should be deployed and rectangular (multi-brick) elements abandoned. Simple closed formulae of integration in multi-dimension domain have been derived. Another specific problem represents the generation of multi-dimensional finite element mesh. Assembling of system global matrices should be subjected to newly composed algorithms due to multi-dimensionality. The system matrices are quite full and no advantages following from their sparse character can be profited from, as is commonly used in conventional FEM applications in 2D/3D problems. After verification of partial algorithms, an illustrative example dealing with a 2DOF non-linear aeroelastic system in combination with random and deterministic excitations is discussed.

Assessment of health surveys: fitting a multidimensional graded response model.

PubMed

Depaoli, Sarah; Tiemensma, Jitske; Felt, John M

The multidimensional graded response model, an item response theory (IRT) model, can be used to improve the assessment of surveys, even when sample sizes are restricted. Typically, health-based survey development utilizes classical statistical techniques (e.g. reliability and factor analysis). In a review of four prominent journals within the field of Health Psychology, we found that IRT-based models were used in less than 10% of the studies examining scale development or assessment. However, implementing IRT-based methods can provide more details about individual survey items, which is useful when determining the final item content of surveys. An example using a quality of life survey for Cushing's syndrome (CushingQoL) highlights the main components for implementing the multidimensional graded response model. Patients with Cushing's syndrome (n = 397) completed the CushingQoL. Results from the multidimensional graded response model supported a 2-subscale scoring process for the survey. All items were deemed as worthy contributors to the survey. The graded response model can accommodate unidimensional or multidimensional scales, be used with relatively lower sample sizes, and is implemented in free software (example code provided in online Appendix). Use of this model can help to improve the quality of health-based scales being developed within the Health Sciences.

The Effect of Multidimensional Motivation Interventions on Cognitive and Behavioral Components of Motivation: Testing Martin's Model

PubMed Central

Pooragha Roodbarde, Fatemeh; Talepasand, Siavash; Rahimian Boogar, Issac

2017-01-01

Objective: The present study aimed at examining the effect of multidimensional motivation interventions based on Martin's model on cognitive and behavioral components of motivation. Method: The research design was prospective with pretest, posttest, and follow-up, and 2 experimental groups. In this study, 90 students (45 participants in the experimental group and 45 in the control group) constituted the sample of the study, and they were selected by available sampling method. Motivation interventions were implemented for fifteen 60-minute sessions 3 times a week, which lasted for about 2 months. Data were analyzed using repeated measures multivariate variance analysis test. Results: The findings revealed that multidimensional motivation interventions resulted in a significant increase in the scores of cognitive components such as self-efficacy, mastery goal, test anxiety, and feeling of lack of control, and behavioral components such as task management. The results of one-month follow-up indicated the stability of the created changes in test anxiety and cognitive strategies; however, no significant difference was found between the 2 groups at the follow-up in self-efficacy, mastery goals, source of control, and motivation. Conclusion: The research evidence indicated that academic motivation is a multidimensional component and is affected by cognitive and behavioral factors; therefore, researchers, teachers, and other authorities should attend to these factors to increase academic motivation. PMID:28659984

The Effect of Multidimensional Motivation Interventions on Cognitive and Behavioral Components of Motivation: Testing Martin's Model.

PubMed

Pooragha Roodbarde, Fatemeh; Talepasand, Siavash; Rahimian Boogar, Issac

2017-04-01

Objective: The present study aimed at examining the effect of multidimensional motivation interventions based on Martin's model on cognitive and behavioral components of motivation. Method: The research design was prospective with pretest, posttest, and follow-up, and 2 experimental groups. In this study, 90 students (45 participants in the experimental group and 45 in the control group) constituted the sample of the study, and they were selected by available sampling method. Motivation interventions were implemented for fifteen 60-minute sessions 3 times a week, which lasted for about 2 months. Data were analyzed using repeated measures multivariate variance analysis test. Results: The findings revealed that multidimensional motivation interventions resulted in a significant increase in the scores of cognitive components such as self-efficacy, mastery goal, test anxiety, and feeling of lack of control, and behavioral components such as task management. The results of one-month follow-up indicated the stability of the created changes in test anxiety and cognitive strategies; however, no significant difference was found between the 2 groups at the follow-up in self-efficacy, mastery goals, source of control, and motivation. Conclusion: The research evidence indicated that academic motivation is a multidimensional component and is affected by cognitive and behavioral factors; therefore, researchers, teachers, and other authorities should attend to these factors to increase academic motivation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fang, X.; Xia, C.; Keppens, R.

We extend our earlier multidimensional, magnetohydrodynamic simulations of coronal rain occurring in magnetic arcades with higher resolution, grid-adaptive computations covering a much longer (>6 hr) time span. We quantify how blob-like condensations forming in situ grow along and across field lines and show that rain showers can occur in limit cycles, here demonstrated for the first time in 2.5D setups. We discuss dynamical, multi-dimensional aspects of the rebound shocks generated by the siphon inflows and quantify the thermodynamics of a prominence–corona transition-region-like structure surrounding the blobs. We point out the correlation between condensation rates and the cross-sectional size of loopmore » systems where catastrophic cooling takes place. We also study the variations of the typical number density, kinetic energy, and temperature while blobs descend, impact, and sink into the transition region. In addition, we explain the mechanisms leading to concurrent upflows while the blobs descend. As a result, there are plenty of shear flows generated with relative velocity difference around 80 km s{sup −1} in our simulations. These shear flows are siphon flows set up by multiple blob dynamics and they in turn affect the deformation of the falling blobs. In particular, we show how shear flows can break apart blobs into smaller fragments, within minutes.« less

Bayesian reconstruction of projection reconstruction NMR (PR-NMR).

PubMed

Yoon, Ji Won

2014-11-01

Projection reconstruction nuclear magnetic resonance (PR-NMR) is a technique for generating multidimensional NMR spectra. A small number of projections from lower-dimensional NMR spectra are used to reconstruct the multidimensional NMR spectra. In our previous work, it was shown that multidimensional NMR spectra are efficiently reconstructed using peak-by-peak based reversible jump Markov chain Monte Carlo (RJMCMC) algorithm. We propose an extended and generalized RJMCMC algorithm replacing a simple linear model with a linear mixed model to reconstruct close NMR spectra into true spectra. This statistical method generates samples in a Bayesian scheme. Our proposed algorithm is tested on a set of six projections derived from the three-dimensional 700 MHz HNCO spectrum of a protein HasA. Copyright © 2014 Elsevier Ltd. All rights reserved.

Solution of system of multidimensional differential equations in X for identification of gold nanoparticles on fibers with elimination of uncertainty

NASA Astrophysics Data System (ADS)

Dobrovolskaya, T. A.; Emelyanov, V. M.; Emelyanov, V. V.

2018-05-01

There are the results of the compilation and solution of a system of multidimensional differential correlation equations of distribution ellipses in the identification of colloidal gold nanoparticles on polyester fibers with multi-dimensional correlation components of Raman polarization spectra. A proposed method is to increase the accuracy and speed of identification of silver nanoparticles on polyester fibers, taking into account the longitudinal and transverse polarization of laser radiation over the entire spectral range, analyzing in sequence and in order simultaneously two peaks along the X-transverse and along the Y-along the fibers. During a solution of the system using a nonlinear quadratic and differential equation with respect to X, an uncertainty arises, the elimination of which is numerical addition Δ = + 0.02985

COREPA-M: NEW MULTI-DIMENSIONAL FUNCTIONALITY OF THE COREPA METHOD

EPA Science Inventory

The COmmon REactivity PAttern (COREPA) method is a recently developed pattern recognition technique accounting for conformational flexibility of chemicals in 3-D quantitative structure-activity relationships (QSARs). The method is based on the assumption that non-congeneric chemi...

Multi-Dimensional Asymptotically Stable 4th Order Accurate Schemes for the Diffusion Equation

NASA Technical Reports Server (NTRS)

Abarbanel, Saul; Ditkowski, Adi

1996-01-01

An algorithm is presented which solves the multi-dimensional diffusion equation on co mplex shapes to 4th-order accuracy and is asymptotically stable in time. This bounded-error result is achieved by constructing, on a rectangular grid, a differentiation matrix whose symmetric part is negative definite. The differentiation matrix accounts for the Dirichlet boundary condition by imposing penalty like terms. Numerical examples in 2-D show that the method is effective even where standard schemes, stable by traditional definitions fail.

An architecture for consolidating multidimensional time-series data onto a common coordinate grid

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shippert, Tim; Gaustad, Krista

Consolidating measurement data for use by data models or in inter-comparison studies frequently requires transforming the data onto a common grid. Standard methods for interpolating multidimensional data are often not appropriate for data with non-homogenous dimensionality, and are hard to implement in a consistent manner for different datastreams. These challenges are increased when dealing with the automated procedures necessary for use with continuous, operational datastreams. In this paper we introduce a method of applying a series of one-dimensional transformations to merge data onto a common grid, examine the challenges of ensuring consistent application of data consolidation methods, present a frameworkmore » for addressing those challenges, and describe the implementation of such a framework for the Atmospheric Radiation Measurement (ARM) program.« less

Reducing seed dependent variability of non-uniformly sampled multidimensional NMR data

NASA Astrophysics Data System (ADS)

Mobli, Mehdi

2015-07-01

The application of NMR spectroscopy to study the structure, dynamics and function of macromolecules requires the acquisition of several multidimensional spectra. The one-dimensional NMR time-response from the spectrometer is extended to additional dimensions by introducing incremented delays in the experiment that cause oscillation of the signal along "indirect" dimensions. For a given dimension the delay is incremented at twice the rate of the maximum frequency (Nyquist rate). To achieve high-resolution requires acquisition of long data records sampled at the Nyquist rate. This is typically a prohibitive step due to time constraints, resulting in sub-optimal data records to the detriment of subsequent analyses. The multidimensional NMR spectrum itself is typically sparse, and it has been shown that in such cases it is possible to use non-Fourier methods to reconstruct a high-resolution multidimensional spectrum from a random subset of non-uniformly sampled (NUS) data. For a given acquisition time, NUS has the potential to improve the sensitivity and resolution of a multidimensional spectrum, compared to traditional uniform sampling. The improvements in sensitivity and/or resolution achieved by NUS are heavily dependent on the distribution of points in the random subset acquired. Typically, random points are selected from a probability density function (PDF) weighted according to the NMR signal envelope. In extreme cases as little as 1% of the data is subsampled. The heavy under-sampling can result in poor reproducibility, i.e. when two experiments are carried out where the same number of random samples is selected from the same PDF but using different random seeds. Here, a jittered sampling approach is introduced that is shown to improve random seed dependent reproducibility of multidimensional spectra generated from NUS data, compared to commonly applied NUS methods. It is shown that this is achieved due to the low variability of the inherent sensitivity of the random subset chosen from a given PDF. Finally, it is demonstrated that metrics used to find optimal NUS distributions are heavily dependent on the inherent sensitivity of the random subset, and such optimisation is therefore less critical when using the proposed sampling scheme.

Multidimensional generalized-ensemble algorithms for complex systems.

PubMed

Mitsutake, Ayori; Okamoto, Yuko

2009-06-07

We give general formulations of the multidimensional multicanonical algorithm, simulated tempering, and replica-exchange method. We generalize the original potential energy function E(0) by adding any physical quantity V of interest as a new energy term. These multidimensional generalized-ensemble algorithms then perform a random walk not only in E(0) space but also in V space. Among the three algorithms, the replica-exchange method is the easiest to perform because the weight factor is just a product of regular Boltzmann-like factors, while the weight factors for the multicanonical algorithm and simulated tempering are not a priori known. We give a simple procedure for obtaining the weight factors for these two latter algorithms, which uses a short replica-exchange simulation and the multiple-histogram reweighting techniques. As an example of applications of these algorithms, we have performed a two-dimensional replica-exchange simulation and a two-dimensional simulated-tempering simulation using an alpha-helical peptide system. From these simulations, we study the helix-coil transitions of the peptide in gas phase and in aqueous solution.

Second-order kinetic model for the sorption of cadmium onto tree fern: a comparison of linear and non-linear methods.

PubMed

Ho, Yuh-Shan

2006-01-01

A comparison was made of the linear least-squares method and a trial-and-error non-linear method of the widely used pseudo-second-order kinetic model for the sorption of cadmium onto ground-up tree fern. Four pseudo-second-order kinetic linear equations are discussed. Kinetic parameters obtained from the four kinetic linear equations using the linear method differed but they were the same when using the non-linear method. A type 1 pseudo-second-order linear kinetic model has the highest coefficient of determination. Results show that the non-linear method may be a better way to obtain the desired parameters.

Reduction and Uncertainty Analysis of Chemical Mechanisms Based on Local and Global Sensitivities

NASA Astrophysics Data System (ADS)

Esposito, Gaetano

Numerical simulations of critical reacting flow phenomena in hypersonic propulsion devices require accurate representation of finite-rate chemical kinetics. The chemical kinetic models available for hydrocarbon fuel combustion are rather large, involving hundreds of species and thousands of reactions. As a consequence, they cannot be used in multi-dimensional computational fluid dynamic calculations in the foreseeable future due to the prohibitive computational cost. In addition to the computational difficulties, it is also known that some fundamental chemical kinetic parameters of detailed models have significant level of uncertainty due to limited experimental data available and to poor understanding of interactions among kinetic parameters. In the present investigation, local and global sensitivity analysis techniques are employed to develop a systematic approach of reducing and analyzing detailed chemical kinetic models. Unlike previous studies in which skeletal model reduction was based on the separate analysis of simple cases, in this work a novel strategy based on Principal Component Analysis of local sensitivity values is presented. This new approach is capable of simultaneously taking into account all the relevant canonical combustion configurations over different composition, temperature and pressure conditions. Moreover, the procedure developed in this work represents the first documented inclusion of non-premixed extinction phenomena, which is of great relevance in hypersonic combustors, in an automated reduction algorithm. The application of the skeletal reduction to a detailed kinetic model consisting of 111 species in 784 reactions is demonstrated. The resulting reduced skeletal model of 37--38 species showed that the global ignition/propagation/extinction phenomena of ethylene-air mixtures can be predicted within an accuracy of 2% of the full detailed model. The problems of both understanding non-linear interactions between kinetic parameters and identifying sources of uncertainty affecting relevant reaction pathways are usually addressed by resorting to Global Sensitivity Analysis (GSA) techniques. In particular, the most sensitive reactions controlling combustion phenomena are first identified using the Morris Method and then analyzed under the Random Sampling -- High Dimensional Model Representation (RS-HDMR) framework. The HDMR decomposition shows that 10% of the variance seen in the extinction strain rate of non-premixed flames is due to second-order effects between parameters, whereas the maximum concentration of acetylene, a key soot precursor, is affected by mostly only first-order contributions. Moreover, the analysis of the global sensitivity indices demonstrates that improving the accuracy of the reaction rates including the vinyl radical, C2H3, can drastically reduce the uncertainty of predicting targeted flame properties. Finally, the back-propagation of the experimental uncertainty of the extinction strain rate to the parameter space is also performed. This exercise, achieved by recycling the numerical solutions of the RS-HDMR, shows that some regions of the parameter space have a high probability of reproducing the experimental value of the extinction strain rate between its own uncertainty bounds. Therefore this study demonstrates that the uncertainty analysis of bulk flame properties can effectively provide information on relevant chemical reactions.

A Century of Enzyme Kinetic Analysis, 1913 to 2013

PubMed Central

Johnson, Kenneth A.

2013-01-01

This review traces the history and logical progression of methods for quantitative analysis of enzyme kinetics from the 1913 Michaelis and Menten paper to the application of modern computational methods today. Following a brief review of methods for fitting steady state kinetic data, modern methods are highlighted for fitting full progress curve kinetics based upon numerical integration of rate equations, including a re-analysis of the original Michaelis-Menten full time course kinetic data. Finally, several illustrations of modern transient state kinetic methods of analysis are shown which enable the elucidation of reactions occurring at the active sites of enzymes in order to relate structure and function. PMID:23850893

Solid-state nanopore detection of protein complexes: applications in healthcare and protein kinetics.

PubMed

Freedman, Kevin J; Bastian, Arangassery R; Chaiken, Irwin; Kim, Min Jun

2013-03-11

Protein conjugation provides a unique look into many biological phenomena and has been used for decades for molecular recognition purposes. In this study, the use of solid-state nanopores for the detection of gp120-associated complexes are investigated. They exhibit monovalent and multivalent binding to anti-gp120 antibody monomer and dimers. In order to investigate the feasibility of many practical applications related to nanopores, detection of specific protein complexes is attempted within a heterogeneous protein sample, and the role of voltage on complexed proteins is researched. It is found that the electric field within the pore can result in unbinding of a freely translocating protein complex within the transient event durations measured experimentally. The strong dependence of the unbinding time with voltage can be used to improve the detection capability of the nanopore system by adding an additional level of specificity that can be probed. These data provide a strong framework for future protein-specific detection schemes, which are shown to be feasible in the realm of a 'real-world' sample and an automated multidimensional method of detecting events. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Non-triglyceride components modulate the fat crystal network of palm kernel oil and coconut oil.

PubMed

Chai, Xiuhang; Meng, Zong; Jiang, Jiang; Cao, Peirang; Liang, Xinyu; Piatko, Michael; Campbell, Shawn; Lo, Seong Koon; Liu, Yuanfa

2018-03-01

PKO and CNO are composed of 97-98% triacylglycerols and 2-3% minor non-triglyceride components (FFA, DAG and MAG). Triglycerides were separated from minor components by chromatographic method. The lipid composition, thermal properties, polymorphism, isothermal crystallization behavior, nanostructure and microstructure of PKO, PKO-TAG, CNO and CNO-TAG were evaluated. Removal of minor components had no effect on lipid composition and equilibrium solid fat contents. However, presence of minor components did increase the slip melting point and promoted the onset of crystallization from DSC crystallization profiles. The thickness of the nanoscale crystals increased with no polymorphic transformation after removing the minor components. Crystallization kinetics revealed that minor components decreased crystal growth rate with higher t 1/2 . Sharp changes in the values of the Avrami constant k and exponent n were observed for all fats around 10°C. Increases in n around 10°C indicated a change from one-dimensional to multi-dimensional growth . From the results of polarized light micrographs, the transformation from the coarser crystal structure to tiny crystal structure occurred in microstructure networks at the action of minor components. Copyright © 2017 Elsevier Ltd. All rights reserved.

Computational Prediction of Excited-State Carbon Tunneling in the Two Steps of Triplet Zimmerman Di-π-Methane Rearrangement.

PubMed

Li, Xin; Liao, Tao; Chung, Lung Wa

2017-11-22

The photoinduced Zimmerman di-π-methane (DPM) rearrangement of polycyclic molecules to form synthetically useful cyclopropane derivatives was found experimentally to proceed in a triplet excited state. We have applied state-of-the-art quantum mechanical methods, including M06-2X, DLPNO-CCSD(T) and variational transition-state theory with multidimensional tunneling corrections, to an investigation of the reaction rates of the two steps in the triplet DPM rearrangement of dibenzobarrelene, benzobarrelene and barrelene. This study predicts a high probability of carbon tunneling in regions around the two consecutive transition states at 200-300 K, and an enhancement in the rates by 104-276/35-67% with carbon tunneling at 200/300 K. The Arrhenius plots of the rate constants were found to be curved at low temperatures. Moreover, the computed 12 C/ 13 C kinetic isotope effects were affected significantly by carbon tunneling and temperature. Our predictions of electronically excited-state carbon tunneling and two consecutive carbon tunneling are unprecedented. Heavy-atom tunneling in some photoinduced reactions with reactive intermediates and narrow barriers can be potentially observed at relatively low temperature in experiments.

Linear and non-linear regression analysis for the sorption kinetics of methylene blue onto activated carbon.

PubMed

Kumar, K Vasanth

2006-10-11

Batch kinetic experiments were carried out for the sorption of methylene blue onto activated carbon. The experimental kinetics were fitted to the pseudo first-order and pseudo second-order kinetics by linear and a non-linear method. The five different types of Ho pseudo second-order expression have been discussed. A comparison of linear least-squares method and a trial and error non-linear method of estimating the pseudo second-order rate kinetic parameters were examined. The sorption process was found to follow a both pseudo first-order kinetic and pseudo second-order kinetic model. Present investigation showed that it is inappropriate to use a type 1 and type pseudo second-order expressions as proposed by Ho and Blanachard et al. respectively for predicting the kinetic rate constants and the initial sorption rate for the studied system. Three correct possible alternate linear expressions (type 2 to type 4) to better predict the initial sorption rate and kinetic rate constants for the studied system (methylene blue/activated carbon) was proposed. Linear method was found to check only the hypothesis instead of verifying the kinetic model. Non-linear regression method was found to be the more appropriate method to determine the rate kinetic parameters.

MODA: a new algorithm to compute optical depths in multidimensional hydrodynamic simulations

NASA Astrophysics Data System (ADS)

Perego, Albino; Gafton, Emanuel; Cabezón, Rubén; Rosswog, Stephan; Liebendörfer, Matthias

2014-08-01

Aims: We introduce the multidimensional optical depth algorithm (MODA) for the calculation of optical depths in approximate multidimensional radiative transport schemes, equally applicable to neutrinos and photons. Motivated by (but not limited to) neutrino transport in three-dimensional simulations of core-collapse supernovae and neutron star mergers, our method makes no assumptions about the geometry of the matter distribution, apart from expecting optically transparent boundaries. Methods: Based on local information about opacities, the algorithm figures out an escape route that tends to minimize the optical depth without assuming any predefined paths for radiation. Its adaptivity makes it suitable for a variety of astrophysical settings with complicated geometry (e.g., core-collapse supernovae, compact binary mergers, tidal disruptions, star formation, etc.). We implement the MODA algorithm into both a Eulerian hydrodynamics code with a fixed, uniform grid and into an SPH code where we use a tree structure that is otherwise used for searching neighbors and calculating gravity. Results: In a series of numerical experiments, we compare the MODA results with analytically known solutions. We also use snapshots from actual 3D simulations and compare the results of MODA with those obtained with other methods, such as the global and local ray-by-ray method. It turns out that MODA achieves excellent accuracy at a moderate computational cost. In appendix we also discuss implementation details and parallelization strategies.

A fast and objective multidimensional kernel density estimation method: fastKDE

DOE PAGES

O'Brien, Travis A.; Kashinath, Karthik; Cavanaugh, Nicholas R.; ...

2016-03-07

Numerous facets of scientific research implicitly or explicitly call for the estimation of probability densities. Histograms and kernel density estimates (KDEs) are two commonly used techniques for estimating such information, with the KDE generally providing a higher fidelity representation of the probability density function (PDF). Both methods require specification of either a bin width or a kernel bandwidth. While techniques exist for choosing the kernel bandwidth optimally and objectively, they are computationally intensive, since they require repeated calculation of the KDE. A solution for objectively and optimally choosing both the kernel shape and width has recently been developed by Bernacchiamore » and Pigolotti (2011). While this solution theoretically applies to multidimensional KDEs, it has not been clear how to practically do so. A method for practically extending the Bernacchia-Pigolotti KDE to multidimensions is introduced. This multidimensional extension is combined with a recently-developed computational improvement to their method that makes it computationally efficient: a 2D KDE on 10 5 samples only takes 1 s on a modern workstation. This fast and objective KDE method, called the fastKDE method, retains the excellent statistical convergence properties that have been demonstrated for univariate samples. The fastKDE method exhibits statistical accuracy that is comparable to state-of-the-science KDE methods publicly available in R, and it produces kernel density estimates several orders of magnitude faster. The fastKDE method does an excellent job of encoding covariance information for bivariate samples. This property allows for direct calculation of conditional PDFs with fastKDE. It is demonstrated how this capability might be leveraged for detecting non-trivial relationships between quantities in physical systems, such as transitional behavior.« less

A hybrid heuristic for the multiple choice multidimensional knapsack problem

NASA Astrophysics Data System (ADS)

Mansi, Raïd; Alves, Cláudio; Valério de Carvalho, J. M.; Hanafi, Saïd

2013-08-01

In this article, a new solution approach for the multiple choice multidimensional knapsack problem is described. The problem is a variant of the multidimensional knapsack problem where items are divided into classes, and exactly one item per class has to be chosen. Both problems are NP-hard. However, the multiple choice multidimensional knapsack problem appears to be more difficult to solve in part because of its choice constraints. Many real applications lead to very large scale multiple choice multidimensional knapsack problems that can hardly be addressed using exact algorithms. A new hybrid heuristic is proposed that embeds several new procedures for this problem. The approach is based on the resolution of linear programming relaxations of the problem and reduced problems that are obtained by fixing some variables of the problem. The solutions of these problems are used to update the global lower and upper bounds for the optimal solution value. A new strategy for defining the reduced problems is explored, together with a new family of cuts and a reformulation procedure that is used at each iteration to improve the performance of the heuristic. An extensive set of computational experiments is reported for benchmark instances from the literature and for a large set of hard instances generated randomly. The results show that the approach outperforms other state-of-the-art methods described so far, providing the best known solution for a significant number of benchmark instances.

Using complex networks towards information retrieval and diagnostics in multidimensional imaging

NASA Astrophysics Data System (ADS)

Banerjee, Soumya Jyoti; Azharuddin, Mohammad; Sen, Debanjan; Savale, Smruti; Datta, Himadri; Dasgupta, Anjan Kr; Roy, Soumen

2015-12-01

We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers.

Using complex networks towards information retrieval and diagnostics in multidimensional imaging.

PubMed

Banerjee, Soumya Jyoti; Azharuddin, Mohammad; Sen, Debanjan; Savale, Smruti; Datta, Himadri; Dasgupta, Anjan Kr; Roy, Soumen

2015-12-02

We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers.

Using complex networks towards information retrieval and diagnostics in multidimensional imaging

PubMed Central

Banerjee, Soumya Jyoti; Azharuddin, Mohammad; Sen, Debanjan; Savale, Smruti; Datta, Himadri; Dasgupta, Anjan Kr; Roy, Soumen

2015-01-01

We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers. PMID:26626047

Evidence against the continuum structure underlying motivation measures derived from self-determination theory.

PubMed

Chemolli, Emanuela; Gagné, Marylène

2014-06-01

Self-determination theory (SDT) proposes a multidimensional conceptualization of motivation in which the different regulations are said to fall along a continuum of self-determination. The continuum has been used as a basis for using a relative autonomy index as a means to create motivational scores. Rasch analysis was used to verify the continuum structure of the Multidimensional Work Motivation Scale and of the Academic Motivation Scale. We discuss the concept of continuum against SDT's conceptualization of motivation and argue against the use of the relative autonomy index on the grounds that evidence for a continuum structure underlying the regulations is weak and because the index is statistically problematic. We suggest exploiting the full richness of SDT's multidimensional conceptualization of motivation through the use of alternative scoring methods when investigating motivational dynamics across life domains.

ULTRA-SHARP nonoscillatory convection schemes for high-speed steady multidimensional flow

NASA Technical Reports Server (NTRS)

Leonard, B. P.; Mokhtari, Simin

1990-01-01

For convection-dominated flows, classical second-order methods are notoriously oscillatory and often unstable. For this reason, many computational fluid dynamicists have adopted various forms of (inherently stable) first-order upwinding over the past few decades. Although it is now well known that first-order convection schemes suffer from serious inaccuracies attributable to artificial viscosity or numerical diffusion under high convection conditions, these methods continue to enjoy widespread popularity for numerical heat transfer calculations, apparently due to a perceived lack of viable high accuracy alternatives. But alternatives are available. For example, nonoscillatory methods used in gasdynamics, including currently popular TVD schemes, can be easily adapted to multidimensional incompressible flow and convective transport. This, in itself, would be a major advance for numerical convective heat transfer, for example. But, as is shown, second-order TVD schemes form only a small, overly restrictive, subclass of a much more universal, and extremely simple, nonoscillatory flux-limiting strategy which can be applied to convection schemes of arbitrarily high order accuracy, while requiring only a simple tridiagonal ADI line-solver, as used in the majority of general purpose iterative codes for incompressible flow and numerical heat transfer. The new universal limiter and associated solution procedures form the so-called ULTRA-SHARP alternative for high resolution nonoscillatory multidimensional steady state high speed convective modelling.

Multi-Dimensional, Mesoscopic Monte Carlo Simulations of Inhomogeneous Reaction-Drift-Diffusion Systems on Graphics-Processing Units

PubMed Central

Vigelius, Matthias; Meyer, Bernd

2012-01-01

For many biological applications, a macroscopic (deterministic) treatment of reaction-drift-diffusion systems is insufficient. Instead, one has to properly handle the stochastic nature of the problem and generate true sample paths of the underlying probability distribution. Unfortunately, stochastic algorithms are computationally expensive and, in most cases, the large number of participating particles renders the relevant parameter regimes inaccessible. In an attempt to address this problem we present a genuine stochastic, multi-dimensional algorithm that solves the inhomogeneous, non-linear, drift-diffusion problem on a mesoscopic level. Our method improves on existing implementations in being multi-dimensional and handling inhomogeneous drift and diffusion. The algorithm is well suited for an implementation on data-parallel hardware architectures such as general-purpose graphics processing units (GPUs). We integrate the method into an operator-splitting approach that decouples chemical reactions from the spatial evolution. We demonstrate the validity and applicability of our algorithm with a comprehensive suite of standard test problems that also serve to quantify the numerical accuracy of the method. We provide a freely available, fully functional GPU implementation. Integration into Inchman, a user-friendly web service, that allows researchers to perform parallel simulations of reaction-drift-diffusion systems on GPU clusters is underway. PMID:22506001

Emotion Recognition from EEG Signals Using Multidimensional Information in EMD Domain.

PubMed

Zhuang, Ning; Zeng, Ying; Tong, Li; Zhang, Chi; Zhang, Hanming; Yan, Bin

2017-01-01

This paper introduces a method for feature extraction and emotion recognition based on empirical mode decomposition (EMD). By using EMD, EEG signals are decomposed into Intrinsic Mode Functions (IMFs) automatically. Multidimensional information of IMF is utilized as features, the first difference of time series, the first difference of phase, and the normalized energy. The performance of the proposed method is verified on a publicly available emotional database. The results show that the three features are effective for emotion recognition. The role of each IMF is inquired and we find that high frequency component IMF1 has significant effect on different emotional states detection. The informative electrodes based on EMD strategy are analyzed. In addition, the classification accuracy of the proposed method is compared with several classical techniques, including fractal dimension (FD), sample entropy, differential entropy, and discrete wavelet transform (DWT). Experiment results on DEAP datasets demonstrate that our method can improve emotion recognition performance.

Anchor-Free Localization Method for Mobile Targets in Coal Mine Wireless Sensor Networks

PubMed Central

Pei, Zhongmin; Deng, Zhidong; Xu, Shuo; Xu, Xiao

2009-01-01

Severe natural conditions and complex terrain make it difficult to apply precise localization in underground mines. In this paper, an anchor-free localization method for mobile targets is proposed based on non-metric multi-dimensional scaling (Multi-dimensional Scaling: MDS) and rank sequence. Firstly, a coal mine wireless sensor network is constructed in underground mines based on the ZigBee technology. Then a non-metric MDS algorithm is imported to estimate the reference nodes’ location. Finally, an improved sequence-based localization algorithm is presented to complete precise localization for mobile targets. The proposed method is tested through simulations with 100 nodes, outdoor experiments with 15 ZigBee physical nodes, and the experiments in the mine gas explosion laboratory with 12 ZigBee nodes. Experimental results show that our method has better localization accuracy and is more robust in underground mines. PMID:22574048

Anchor-free localization method for mobile targets in coal mine wireless sensor networks.

PubMed

Pei, Zhongmin; Deng, Zhidong; Xu, Shuo; Xu, Xiao

2009-01-01

Severe natural conditions and complex terrain make it difficult to apply precise localization in underground mines. In this paper, an anchor-free localization method for mobile targets is proposed based on non-metric multi-dimensional scaling (Multi-dimensional Scaling: MDS) and rank sequence. Firstly, a coal mine wireless sensor network is constructed in underground mines based on the ZigBee technology. Then a non-metric MDS algorithm is imported to estimate the reference nodes' location. Finally, an improved sequence-based localization algorithm is presented to complete precise localization for mobile targets. The proposed method is tested through simulations with 100 nodes, outdoor experiments with 15 ZigBee physical nodes, and the experiments in the mine gas explosion laboratory with 12 ZigBee nodes. Experimental results show that our method has better localization accuracy and is more robust in underground mines.

Multidimensional gray-wavelet processing in interferometric fiber-optic gyroscopes

NASA Astrophysics Data System (ADS)

Yang, Yi; Wang, Zinan; Peng, Chao; Li, Zhengbin

2013-11-01

A multidimensional signal processing method for a single interferometric fiber-optic gyroscope (IFOG) is proposed, to the best of our knowledge, for the first time. The proposed method, based on a novel IFOG structure with quadrature demodulation, combines a multidimensional gray model (GM) and a wavelet compression technique for noise suppression and sensitivity enhancement. In the IFOG, two series of measured rotation rates are obtained simultaneously: an in-phase component and a quadrature component. Together with the traditionally measured rate, the three measured rates are processed by the combined gray-wavelet method. Simulations show that the intensity noise and non-reciprocal phase fluctuations are effectively suppressed by this method. Experimental comparisons with a one-dimensional GM(1, 1) model show that the proposed three-dimensional method achieves much better denoising performance. This advantage is validated by the Allan variance analysis: in a low-SNR (signal-to-noise ratio) experiment, our method reduces the angle random walk (ARW) and the bias instability (BI) from 1 × 10-2 deg h-1/2 and 3 × 10-2 deg h-1 to 1 × 10-3 deg h-1/2 and 3 × 10-3 deg h-1, respectively; in a high-SNR experiment, our method reduces the ARW and the BI from 9 × 10-4 deg h-1/2 and 5 × 10-3 deg h-1 to 4 × 10-4 deg h-1/2 and 3 × 10-3 deg h-1, respectively. Further, our method increases the dimension of the state-of-the-art IFOG technique from one to three, thus obtaining higher IFOG sensitivity and stability by exploiting the increase in available information.

Effect of asthma on falling into poverty: the overlooked costs of illness.

PubMed

Callander, Emily J; Schofield, Deborah J

2015-05-01

Studies on the indirect costs of asthma have taken a narrow view of how the condition affects the living standards of patients by examining only the association with employment and income. To build on the current cost-of-illness literature and identify whether having asthma is associated with an increased risk of poverty, thus giving a more complete picture of the costs of asthma to individuals and society. Longitudinal analysis of the nationally representative Household Income and Labour Dynamics in Australian survey to estimate the relative risk of income poverty, multidimensional poverty, and long-term multidimensional poverty between 2007 and 2012 and population attributable risk method to estimate the proportion of poverty between 2007 and 2012 directly attributable to asthma. No significant difference was found in the risk of falling into income poverty between those with and without asthma (P = .07). Having asthma increased the risk of falling into multidimensional poverty by 1.35 (95% confidence interval [CI], 1.01-1.83) and the risk of falling into chronic multidimensional poverty by 2.22 (95% CI, 1.20-4.10). Between 2007 and 2012, a total of 5.2% of income poverty cases (95% CI, 5.1%-5.4%), 7.8% of multidimensional poverty cases (95% CI, 7.7%-8.0%), and 19.6% of chronic multidimensional poverty cases (95% CI, 19.2%-20.0%) can be attributed to asthma. Asthma is associated with an increased risk of falling into poverty. This should be taken into consideration when considering the suitability of different treatment options for patients with asthma. Copyright © 2015 American College of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

An architecture for consolidating multidimensional time-series data onto a common coordinate grid

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shippert, Tim; Gaustad, Krista

In this paper, consolidating measurement data for use by data models or in inter-comparison studies frequently requires transforming the data onto a common grid. Standard methods for interpolating multidimensional data are often not appropriate for data with non-homogenous dimensionality, and are hard to implement in a consistent manner for different datastreams. In addition, these challenges are increased when dealing with the automated procedures necessary for use with continuous, operational datastreams. In this paper we introduce a method of applying a series of one-dimensional transformations to merge data onto a common grid, examine the challenges of ensuring consistent application of datamore » consolidation methods, present a framework for addressing those challenges, and describe the implementation of such a framework for the Atmospheric Radiation Measurement (ARM) program.« less

High-Order Semi-Discrete Central-Upwind Schemes for Multi-Dimensional Hamilton-Jacobi Equations

NASA Technical Reports Server (NTRS)

Bryson, Steve; Levy, Doron; Biegel, Bryan (Technical Monitor)

2002-01-01

We present the first fifth order, semi-discrete central upwind method for approximating solutions of multi-dimensional Hamilton-Jacobi equations. Unlike most of the commonly used high order upwind schemes, our scheme is formulated as a Godunov-type scheme. The scheme is based on the fluxes of Kurganov-Tadmor and Kurganov-Tadmor-Petrova, and is derived for an arbitrary number of space dimensions. A theorem establishing the monotonicity of these fluxes is provided. The spacial discretization is based on a weighted essentially non-oscillatory reconstruction of the derivative. The accuracy and stability properties of our scheme are demonstrated in a variety of examples. A comparison between our method and other fifth-order schemes for Hamilton-Jacobi equations shows that our method exhibits smaller errors without any increase in the complexity of the computations.

An architecture for consolidating multidimensional time-series data onto a common coordinate grid

DOE PAGES

Shippert, Tim; Gaustad, Krista

2016-12-16

In this paper, consolidating measurement data for use by data models or in inter-comparison studies frequently requires transforming the data onto a common grid. Standard methods for interpolating multidimensional data are often not appropriate for data with non-homogenous dimensionality, and are hard to implement in a consistent manner for different datastreams. In addition, these challenges are increased when dealing with the automated procedures necessary for use with continuous, operational datastreams. In this paper we introduce a method of applying a series of one-dimensional transformations to merge data onto a common grid, examine the challenges of ensuring consistent application of datamore » consolidation methods, present a framework for addressing those challenges, and describe the implementation of such a framework for the Atmospheric Radiation Measurement (ARM) program.« less

A Multidimensional Analysis Tool for Visualizing Online Interactions

ERIC Educational Resources Information Center

Kim, Minjeong; Lee, Eunchul

2012-01-01

This study proposes and verifies the performance of an analysis tool for visualizing online interactions. A review of the most widely used methods for analyzing online interactions, including quantitative analysis, content analysis, and social network analysis methods, indicates these analysis methods have some limitations resulting from their…

A century of enzyme kinetic analysis, 1913 to 2013.

PubMed

Johnson, Kenneth A

2013-09-02

This review traces the history and logical progression of methods for quantitative analysis of enzyme kinetics from the 1913 Michaelis and Menten paper to the application of modern computational methods today. Following a brief review of methods for fitting steady state kinetic data, modern methods are highlighted for fitting full progress curve kinetics based upon numerical integration of rate equations, including a re-analysis of the original Michaelis-Menten full time course kinetic data. Finally, several illustrations of modern transient state kinetic methods of analysis are shown which enable the elucidation of reactions occurring at the active sites of enzymes in order to relate structure and function. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Approximation Methods in Multidimensional Filter Design and Related Problems Encountered in Multidimensional System Design.

DTIC Science & Technology

1983-03-21

zero , it is necessary that B M(0) be nonzero. In the case considered here, B M(0) is taken to be nonsingula and withot loss of generality it may be set...452. (c.51 D. Levin, " General order Padd type rational approximants defined from a double power series," J. Inst. Maths. Applics., 18, 1976, pp. 1-8...common zeros in the closed unit bidisc, U- 2 . The 2-D setting provides a nice theoretical framework for generalization of these stabilization results to

Self-consistent multidimensional electron kinetic model for inductively coupled plasma sources

NASA Astrophysics Data System (ADS)

Dai, Fa Foster

Inductively coupled plasma (ICP) sources have received increasing interest in microelectronics fabrication and lighting industry. In 2-D configuration space (r, z) and 2-D velocity domain (νθ,νz), a self- consistent electron kinetic analytic model is developed for various ICP sources. The electromagnetic (EM) model is established based on modal analysis, while the kinetic analysis gives the perturbed Maxwellian distribution of electrons by solving Boltzmann-Vlasov equation. The self- consistent algorithm combines the EM model and the kinetic analysis by updating their results consistently until the solution converges. The closed-form solutions in the analytical model provide rigorous and fast computing for the EM fields and the electron kinetic behavior. The kinetic analysis shows that the RF energy in an ICP source is extracted by a collisionless dissipation mechanism, if the electron thermovelocity is close to the RF phase velocities. A criterion for collisionless damping is thus given based on the analytic solutions. To achieve uniformly distributed plasma for plasma processing, we propose a novel discharge structure with both planar and vertical coil excitations. The theoretical results demonstrate improved uniformity for the excited azimuthal E-field in the chamber. Non-monotonic spatial decay in electric field and space current distributions was recently observed in weakly- collisional plasmas. The anomalous skin effect is found to be responsible for this phenomenon. The proposed model successfully models the non-monotonic spatial decay effect and achieves good agreements with the measurements for different applied RF powers. The proposed analytical model is compared with other theoretical models and different experimental measurements. The developed model is also applied to two kinds of ICP discharges used for electrodeless light sources. One structure uses a vertical internal coil antenna to excite plasmas and another has a metal shield to prevent the electromagnetic radiation. The theoretical results delivered by the proposed model agree quite well with the experimental measurements in many aspects. Therefore, the proposed self-consistent model provides an efficient and reliable means for designing ICP sources in various applications such as VLSI fabrication and electrodeless light sources.

How Geochemistry Provides Habitability: A Case Study of Iron Oxidation

NASA Astrophysics Data System (ADS)

St Clair, B.; Shock, E.

2016-12-01

Two things have to be true for chemotrophic microbes to gain chemical energy from their environment. First, there must be a source of energy, provided by compounds in differing oxidation states that are out of thermodynamic equilibrium with one another. Second, there must be mechanistic difficulties that are keeping those compounds from reacting, preventing chemical energy from dissipating on its own. Using this energetic reference frame, geochemical habitability requires the combined presence of energy sources and kinetic barriers, which are determined by numerous variables including temperature, pH, and concentrations of reactants and products. Here we present habitable geochemical space visually as habitability diagrams. As an example, the pH and temperature ranges that can sustain life for a specific reaction can be delineated by the aforementioned kinetic and energetic boundaries, together with commonly attainable pH / temperatures of environments at Earth's surface. Other habitability diagrams can be constructed for any combination of relevant geochemical variables to better illustrate the inherently multidimensional problem. We have chosen iron oxidation reactions to illustrate this point, as kinetic and energetic boundaries can be found at conditions readily attainable in natural systems. By calculating energy availability (as affinity, A) in each system from compositional data where concentrations of all reactants and products are known, the energy boundary is defined by A=0. Evaluating the kinetic boundary means measuring the relative rates of the biotic and abiotic processes in situ, which we have done in Yellowstone hot springs, acid mine drainage in Arizona, and cold springs in the Swiss Alps. Many experiments have yielded biological rates, and all have yielded abiotic rates, which range from inconsequential to rates too rapid for biology to compete. These results encompass both sides of the kinetic boundary, defining its trajectory. When plotted in pH and T space, this boundary is pH 7.7 at 10°C but decreases to pH 5.5 at 90°C. This tool for visualizing habitability helps quantify extreme environments as those near the kinetic or thermodynamic limits.

Design and Analysis of a Formation Flying System for the Cross-Scale Mission Concept

NASA Technical Reports Server (NTRS)

Cornara, Stefania; Bastante, Juan C.; Jubineau, Franck

2007-01-01

The ESA-funded "Cross-Scale Technology Reference Study has been carried out with the primary aim to identify and analyse a mission concept for the investigation of fundamental space plasma processes that involve dynamical non-linear coupling across multiple length scales. To fulfill this scientific mission goal, a constellation of spacecraft is required, flying in loose formations around the Earth and sampling three characteristic plasma scale distances simultaneously, with at least two satellites per scale: electron kinetic (10 km), ion kinetic (100-2000 km), magnetospheric fluid (3000-15000 km). The key Cross-Scale mission drivers identified are the number of S/C, the space segment configuration, the reference orbit design, the transfer and deployment strategy, the inter-satellite localization and synchronization process and the mission operations. This paper presents a comprehensive overview of the mission design and analysis for the Cross-Scale concept and outlines a technically feasible mission architecture for a multi-dimensional investigation of space plasma phenomena. The main effort has been devoted to apply a thorough mission-level trade-off approach and to accomplish an exhaustive analysis, so as to allow the characterization of a wide range of mission requirements and design solutions.

Patterns of Stochastic Behavior in Dynamically Unstable High-Dimensional Biochemical Networks

PubMed Central

Rosenfeld, Simon

2009-01-01

The question of dynamical stability and stochastic behavior of large biochemical networks is discussed. It is argued that stringent conditions of asymptotic stability have very little chance to materialize in a multidimensional system described by the differential equations of chemical kinetics. The reason is that the criteria of asymptotic stability (Routh-Hurwitz, Lyapunov criteria, Feinberg’s Deficiency Zero theorem) would impose the limitations of very high algebraic order on the kinetic rates and stoichiometric coefficients, and there are no natural laws that would guarantee their unconditional validity. Highly nonlinear, dynamically unstable systems, however, are not necessarily doomed to collapse, as a simple Jacobian analysis would suggest. It is possible that their dynamics may assume the form of pseudo-random fluctuations quite similar to a shot noise, and, therefore, their behavior may be described in terms of Langevin and Fokker-Plank equations. We have shown by simulation that the resulting pseudo-stochastic processes obey the heavy-tailed Generalized Pareto Distribution with temporal sequence of pulses forming the set of constituent-specific Poisson processes. Being applied to intracellular dynamics, these properties are naturally associated with burstiness, a well documented phenomenon in the biology of gene expression. PMID:19838330

Transition path theory analysis of c-Src kinase activation

PubMed Central

Meng, Yilin; Shukla, Diwakar; Pande, Vijay S.; Roux, Benoît

2016-01-01

Nonreceptor tyrosine kinases of the Src family are large multidomain allosteric proteins that are crucial to cellular signaling pathways. In a previous study, we generated a Markov state model (MSM) to simulate the activation of c-Src catalytic domain, used as a prototypical tyrosine kinase. The long-time kinetics of transition predicted by the MSM was in agreement with experimental observations. In the present study, we apply the framework of transition path theory (TPT) to the previously constructed MSM to characterize the main features of the activation pathway. The analysis indicates that the activating transition, in which the activation loop first opens up followed by an inward rotation of the αC-helix, takes place via a dense set of intermediate microstates distributed within a fairly broad “transition tube” in a multidimensional conformational subspace connecting the two end-point conformations. Multiple microstates with negligible equilibrium probabilities carry a large transition flux associated with the activating transition, which explains why extensive conformational sampling is necessary to accurately determine the kinetics of activation. Our results suggest that the combination of MSM with TPT provides an effective framework to represent conformational transitions in complex biomolecular systems. PMID:27482115

Chemometric Strategies for Peak Detection and Profiling from Multidimensional Chromatography.

PubMed

Navarro-Reig, Meritxell; Bedia, Carmen; Tauler, Romà; Jaumot, Joaquim

2018-04-03

The increasing complexity of omics research has encouraged the development of new instrumental technologies able to deal with these challenging samples. In this way, the rise of multidimensional separations should be highlighted due to the massive amounts of information that provide with an enhanced analyte determination. Both proteomics and metabolomics benefit from this higher separation capacity achieved when different chromatographic dimensions are combined, either in LC or GC. However, this vast quantity of experimental information requires the application of chemometric data analysis strategies to retrieve this hidden knowledge, especially in the case of nontargeted studies. In this work, the most common chemometric tools and approaches for the analysis of this multidimensional chromatographic data are reviewed. First, different options for data preprocessing and enhancement of the instrumental signal are introduced. Next, the most used chemometric methods for the detection of chromatographic peaks and the resolution of chromatographic and spectral contributions (profiling) are presented. The description of these data analysis approaches is complemented with enlightening examples from omics fields that demonstrate the exceptional potential of the combination of multidimensional separation techniques and chemometric tools of data analysis. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of a New Multidimensional Individual and Interpersonal Resilience Measure for Older Adults

PubMed Central

Martin, A’verria Sirkin; Distelberg, Brian; Palmer, Barton W.; Jeste, Dilip V.

2015-01-01

Objectives Develop an empirically grounded measure that can be used to assess family and individual resilience in a population of older adults (aged 50-99). Methods Cross-sectional, self-report data from 1,006 older adults were analyzed in two steps. The total sample was split into two sub-samples and the first step identified the underlying latent structure through principal component Exploratory Factor Analysis (EFA). The second step utilized the second half of the sample to validate the derived latent structure through Confirmatory Factor Analysis (CFA). Results EFA produced an eight-factor structure that appeared clinically relevant for measuring the multidimensional nature of resilience. Factors included self-efficacy, access to social support network, optimism, perceived economic and social resources, spirituality and religiosity, relational accord, emotional expression and communication, and emotional regulation. CFA confirmed the eight-factor structure previously achieved with covariance between each of the factors. Based on these analyses we developed the Multidimensional Individual and Interpersonal Resilience Measure (MIIRM), a broad assessment of resilience for older adults. Conclusion This study highlights the multidimensional nature of resilience and introduces an individual and interpersonal resilience measure developed for older adults which is grounded in the individual and family resilience literature. PMID:24787701

Implicitly causality enforced solution of multidimensional transient photon transport equation.

PubMed

Handapangoda, Chintha C; Premaratne, Malin

2009-12-21

A novel method for solving the multidimensional transient photon transport equation for laser pulse propagation in biological tissue is presented. A Laguerre expansion is used to represent the time dependency of the incident short pulse. Owing to the intrinsic causal nature of Laguerre functions, our technique automatically always preserve the causality constrains of the transient signal. This expansion of the radiance using a Laguerre basis transforms the transient photon transport equation to the steady state version. The resulting equations are solved using the discrete ordinates method, using a finite volume approach. Therefore, our method enables one to handle general anisotropic, inhomogeneous media using a single formulation but with an added degree of flexibility owing to the ability to invoke higher-order approximations of discrete ordinate quadrature sets. Therefore, compared with existing strategies, this method offers the advantage of representing the intensity with a high accuracy thus minimizing numerical dispersion and false propagation errors. The application of the method to one, two and three dimensional geometries is provided.

A MUSIC-based method for SSVEP signal processing.

PubMed

Chen, Kun; Liu, Quan; Ai, Qingsong; Zhou, Zude; Xie, Sheng Quan; Meng, Wei

2016-03-01

The research on brain computer interfaces (BCIs) has become a hotspot in recent years because it offers benefit to disabled people to communicate with the outside world. Steady state visual evoked potential (SSVEP)-based BCIs are more widely used because of higher signal to noise ratio and greater information transfer rate compared with other BCI techniques. In this paper, a multiple signal classification based method was proposed for multi-dimensional SSVEP feature extraction. 2-second data epochs from four electrodes achieved excellent accuracy rates including idle state detection. In some asynchronous mode experiments, the recognition accuracy reached up to 100%. The experimental results showed that the proposed method attained good frequency resolution. In most situations, the recognition accuracy was higher than canonical correlation analysis, which is a typical method for multi-channel SSVEP signal processing. Also, a virtual keyboard was successfully controlled by different subjects in an unshielded environment, which proved the feasibility of the proposed method for multi-dimensional SSVEP signal processing in practical applications.

Data analytics and parallel-coordinate materials property charts

NASA Astrophysics Data System (ADS)

Rickman, Jeffrey M.

2018-01-01

It is often advantageous to display material properties relationships in the form of charts that highlight important correlations and thereby enhance our understanding of materials behavior and facilitate materials selection. Unfortunately, in many cases, these correlations are highly multidimensional in nature, and one typically employs low-dimensional cross-sections of the property space to convey some aspects of these relationships. To overcome some of these difficulties, in this work we employ methods of data analytics in conjunction with a visualization strategy, known as parallel coordinates, to represent better multidimensional materials data and to extract useful relationships among properties. We illustrate the utility of this approach by the construction and systematic analysis of multidimensional materials properties charts for metallic and ceramic systems. These charts simplify the description of high-dimensional geometry, enable dimensional reduction and the identification of significant property correlations and underline distinctions among different materials classes.

Assessing the multidimensionality of coastal erosion risks: public participation and multicriteria analysis in a Mediterranean coastal system.

PubMed

Roca, Elisabet; Gamboa, Gonzalo; Tàbara, J David

2008-04-01

The complex and multidimensional nature of coastal erosion risks makes it necessary to move away from single-perspective assessment and management methods that have conventionally predominated in coastal management. This article explores the suitability of participatory multicriteria analysis (MCA) for improving the integration of diverse expertises and values and enhancing the social-ecological robustness of the processes that lead to the definition of relevant policy options to deal with those risks. We test this approach in the Mediterranean coastal locality of Lido de Sète in France. Results show that the more adaptive alternatives such as "retreating the shoreline" were preferred by our selected stakeholders to those corresponding to "protecting the shoreline" and the business as usual proposals traditionally put forward by experts and policymakers on these matters. Participative MCA contributed to represent coastal multidimensionality, elicit and integrate different views and preferences, facilitated knowledge exchange, and allowed highlighting existing uncertainties.

The pursuit of happiness measurement: a psychometric model based on psychophysiological correlates.

PubMed

Pietro, Cipresso; Silvia, Serino; Giuseppe, Riva

2014-01-01

Everyone is interested in the pursuit of happiness, but the real problem for the researchers is how to measure it. Our aim was to deeply investigate happiness measurement through biomedical signals, using psychophysiological methods to objectify the happiness experiences measurements. The classic valence-arousal model of affective states to study happiness has been extensively used in psychophysiology. However, really few studies considered a real combination of these two dimensions and no study further investigated multidimensional models. More, most studies focused mainly on self-report to measure happiness and a deeper psychophysiological investigation on the dimensions of such an experience is still missing. A multidimensional model of happiness is presented and both the dimensions and the measures extracted within each dimension are comprehensively explained. This multidimensional model aims at being a milestone for future systematic study on psychophysiology of happiness and affective states.

Variational calculation of macrostate transition rates

NASA Astrophysics Data System (ADS)

Ulitsky, Alex; Shalloway, David

1998-08-01

We develop the macrostate variational method (MVM) for computing reaction rates of diffusive conformational transitions in multidimensional systems by a variational coarse-grained "macrostate" decomposition of the Smoluchowski equation. MVM uses multidimensional Gaussian packets to identify and focus computational effort on the "transition region," a localized, self-consistently determined region in conformational space positioned roughly between the macrostates. It also determines the "transition direction" which optimally specifies the projected potential of mean force for mean first-passage time calculations. MVM is complementary to variational transition state theory in that it can efficiently solve multidimensional problems but does not accommodate memory-friction effects. It has been tested on model 1- and 2-dimensional potentials and on the 12-dimensional conformational transition between the isoforms of a microcluster of six-atoms having only van der Waals interactions. Comparison with Brownian dynamics calculations shows that MVM obtains equivalent results at a fraction of the computational cost.

Multidimensional supersymmetric quantum mechanics: spurious states for the tensor sector two Hamiltonian.

PubMed

Chou, Chia-Chun; Kouri, Donald J

2013-04-25

We show that there exist spurious states for the sector two tensor Hamiltonian in multidimensional supersymmetric quantum mechanics. For one-dimensional supersymmetric quantum mechanics on an infinite domain, the sector one and two Hamiltonians have identical spectra with the exception of the ground state of the sector one. For tensorial multidimensional supersymmetric quantum mechanics, there exist normalizable spurious states for the sector two Hamiltonian with energy equal to the ground state energy of the sector one. These spurious states are annihilated by the adjoint charge operator, and hence, they do not correspond to physical states for the original Hamiltonian. The Hermitian property of the sector two Hamiltonian implies the orthogonality between spurious and physical states. In addition, we develop a method for construction of a specific form of the spurious states for any quantum system and also generate several spurious states for a two-dimensional anharmonic oscillator system and for the hydrogen atom.

Identity, Intersectionality, and Mixed-Methods Approaches

ERIC Educational Resources Information Center

Harper, Casandra E.

2011-01-01

In this article, the author argues that current strategies to study and understand students' identities fall short of fully capturing their complexity. A multi-dimensional perspective and a mixed-methods approach can reveal nuance that is missed with current approaches. The author offers an illustration of how mixed-methods research can promote a…

Mathematical Formulation of Multivariate Euclidean Models for Discrimination Methods.

ERIC Educational Resources Information Center

Mullen, Kenneth; Ennis, Daniel M.

1987-01-01

Multivariate models for the triangular and duo-trio methods are described, and theoretical methods are compared to a Monte Carlo simulation. Implications are discussed for a new theory of multidimensional scaling which challenges the traditional assumption that proximity measures and perceptual distances are monotonically related. (Author/GDC)

Quasiballistic heat removal from small sources studied from first principles

NASA Astrophysics Data System (ADS)

Vermeersch, Bjorn; Mingo, Natalio

2018-01-01

Heat sources whose characteristic dimension R is comparable to phonon mean free paths display thermal resistances that exceed conventional diffusive predictions. This has direct implications to (opto)electronics thermal management and phonon spectroscopy. Theoretical analyses have so far limited themselves to particular experimental configurations. Here, we build upon the multidimensional Boltzmann transport equation (BTE) to derive universal expressions for the apparent conductivity suppression S (R ) =κeff(R ) /κbulk experienced by radially symmetric 2D and 3D sources. In striking analogy to cross-plane heat conduction in thin films, a distinct quasiballistic regime emerges between ballistic (κeff˜R ) and diffusive (κeff≃κbulk ) asymptotes that displays a logarithmic dependence κeff˜ln(R ) in single crystals and fractional power dependence κeff˜R2 -α in alloys (with α the Lévy superdiffusion exponent). Analytical solutions and Monte Carlo simulations for spherical and circular heat sources in Si, GaAs, Si0.99Ge0.01 , and Si0.82Ge0.18 , all carried out from first principles, confirm the predicted generic tendencies. Contrary to the thin film case, common approximations like kinetic theory estimates κeff≃∑Sωgreyκω and modified Fourier temperature curves perform relatively poorly. Up to threefold deviations from the BTE solutions for sub-100 nm sources underline the need for rigorous treatment of multidimensional nondiffusive transport.

Analysis of precipitation data in Bangladesh through hierarchical clustering and multidimensional scaling

NASA Astrophysics Data System (ADS)

Rahman, Md. Habibur; Matin, M. A.; Salma, Umma

2017-12-01

The precipitation patterns of seventeen locations in Bangladesh from 1961 to 2014 were studied using a cluster analysis and metric multidimensional scaling. In doing so, the current research applies four major hierarchical clustering methods to precipitation in conjunction with different dissimilarity measures and metric multidimensional scaling. A variety of clustering algorithms were used to provide multiple clustering dendrograms for a mixture of distance measures. The dendrogram of pre-monsoon rainfall for the seventeen locations formed five clusters. The pre-monsoon precipitation data for the areas of Srimangal and Sylhet were located in two clusters across the combination of five dissimilarity measures and four hierarchical clustering algorithms. The single linkage algorithm with Euclidian and Manhattan distances, the average linkage algorithm with the Minkowski distance, and Ward's linkage algorithm provided similar results with regard to monsoon precipitation. The results of the post-monsoon and winter precipitation data are shown in different types of dendrograms with disparate combinations of sub-clusters. The schematic geometrical representations of the precipitation data using metric multidimensional scaling showed that the post-monsoon rainfall of Cox's Bazar was located far from those of the other locations. The results of a box-and-whisker plot, different clustering techniques, and metric multidimensional scaling indicated that the precipitation behaviour of Srimangal and Sylhet during the pre-monsoon season, Cox's Bazar and Sylhet during the monsoon season, Maijdi Court and Cox's Bazar during the post-monsoon season, and Cox's Bazar and Khulna during the winter differed from those at other locations in Bangladesh.

On simplified application of multidimensional Savitzky-Golay filters and differentiators

NASA Astrophysics Data System (ADS)

Shekhar, Chandra

2016-02-01

I propose a simplified approach for multidimensional Savitzky-Golay filtering, to enable its fast and easy implementation in scientific and engineering applications. The proposed method, which is derived from a generalized framework laid out by Thornley (D. J. Thornley, "Novel anisotropic multidimensional convolution filters for derivative estimation and reconstruction" in Proceedings of International Conference on Signal Processing and Communications, November 2007), first transforms any given multidimensional problem into a unique one, by transforming coordinates of the sampled data nodes to unity-spaced, uniform data nodes, and then performs filtering and calculates partial derivatives on the unity-spaced nodes. It is followed by transporting the calculated derivatives back onto the original data nodes by using the chain rule of differentiation. The burden to performing the most cumbersome task, which is to carry out the filtering and to obtain derivatives on the unity-spaced nodes, is almost eliminated by providing convolution coefficients for a number of convolution kernel sizes and polynomial orders, up to four spatial dimensions. With the availability of the convolution coefficients, the task of filtering at a data node reduces merely to multiplication of two known matrices. Simplified strategies to adequately address near-boundary data nodes and to calculate partial derivatives there are also proposed. Finally, the proposed methodologies are applied to a three-dimensional experimentally obtained data set, which shows that multidimensional Savitzky-Golay filters and differentiators perform well in both the internal and the near-boundary regions of the domain.

Diagnosis and treatment of unconsummated marriage in an Iranian couple.

PubMed

Bokaie, Mahshid; Khalesi, Zahra Bostani; Yasini-Ardekani, Seyed Mojtaba

2017-09-01

Unconsummated marriage is a problem among couples who would not be able to perform natural sexual intercourse and vaginal penetration. This disorder is more common in developing countries and sometimes couples would come up with non-technical and non-scientific methods to overcome their problem. Multi-dimensional approach and narrative exposure therapy used in this case. This study would report a case of unconsummated marriage between a couple after 6 years. The main problem of this couple was vaginismus and post-traumatic stress. Treatment with multi-dimensional approach for this couple included methods like narrative exposure therapy, educating the anatomy of female and male reproductive system, correcting misconceptions, educating foreplay, educating body exploring and non-sexual and sexual massage and penetrating the vagina first by women finger and then men's after relaxation. The entire stages of the treatment lasted for four sessions and at the one-month follow-up couple's satisfaction was desirable. Unconsummated marriage is one of the main sexual problems; it is more common in developing countries than developed countries and cultural factors are effective on intensifying this disorder. The use of multi-dimensional approach in this study led to expedite diagnosis and treatment of vaginismus.

A Reduced-Order Model for Efficient Simulation of Synthetic Jet Actuators

NASA Technical Reports Server (NTRS)

Yamaleev, Nail K.; Carpenter, Mark H.

2003-01-01

A new reduced-order model of multidimensional synthetic jet actuators that combines the accuracy and conservation properties of full numerical simulation methods with the efficiency of simplified zero-order models is proposed. The multidimensional actuator is simulated by solving the time-dependent compressible quasi-1-D Euler equations, while the diaphragm is modeled as a moving boundary. The governing equations are approximated with a fourth-order finite difference scheme on a moving mesh such that one of the mesh boundaries coincides with the diaphragm. The reduced-order model of the actuator has several advantages. In contrast to the 3-D models, this approach provides conservation of mass, momentum, and energy. Furthermore, the new method is computationally much more efficient than the multidimensional Navier-Stokes simulation of the actuator cavity flow, while providing practically the same accuracy in the exterior flowfield. The most distinctive feature of the present model is its ability to predict the resonance characteristics of synthetic jet actuators; this is not practical when using the 3-D models because of the computational cost involved. Numerical results demonstrating the accuracy of the new reduced-order model and its limitations are presented.

Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers.

PubMed

Borchani, Hanen; Bielza, Concha; Toro, Carlos; Larrañaga, Pedro

2013-03-01

Our aim is to use multi-dimensional Bayesian network classifiers in order to predict the human immunodeficiency virus type 1 (HIV-1) reverse transcriptase and protease inhibitors given an input set of respective resistance mutations that an HIV patient carries. Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models especially designed to solve multi-dimensional classification problems, where each input instance in the data set has to be assigned simultaneously to multiple output class variables that are not necessarily binary. In this paper, we introduce a new method, named MB-MBC, for learning MBCs from data by determining the Markov blanket around each class variable using the HITON algorithm. Our method is applied to both reverse transcriptase and protease data sets obtained from the Stanford HIV-1 database. Regarding the prediction of antiretroviral combination therapies, the experimental study shows promising results in terms of classification accuracy compared with state-of-the-art MBC learning algorithms. For reverse transcriptase inhibitors, we get 71% and 11% in mean and global accuracy, respectively; while for protease inhibitors, we get more than 84% and 31% in mean and global accuracy, respectively. In addition, the analysis of MBC graphical structures lets us gain insight into both known and novel interactions between reverse transcriptase and protease inhibitors and their respective resistance mutations. MB-MBC algorithm is a valuable tool to analyze the HIV-1 reverse transcriptase and protease inhibitors prediction problem and to discover interactions within and between these two classes of inhibitors. Copyright © 2012 Elsevier B.V. All rights reserved.

Joint mapping of genes and conditions via multidimensional unfolding analysis

PubMed Central

Van Deun, Katrijn; Marchal, Kathleen; Heiser, Willem J; Engelen, Kristof; Van Mechelen, Iven

2007-01-01

Background Microarray compendia profile the expression of genes in a number of experimental conditions. Such data compendia are useful not only to group genes and conditions based on their similarity in overall expression over profiles but also to gain information on more subtle relations between genes and conditions. Getting a clear visual overview of all these patterns in a single easy-to-grasp representation is a useful preliminary analysis step: We propose to use for this purpose an advanced exploratory method, called multidimensional unfolding. Results We present a novel algorithm for multidimensional unfolding that overcomes both general problems and problems that are specific for the analysis of gene expression data sets. Applying the algorithm to two publicly available microarray compendia illustrates its power as a tool for exploratory data analysis: The unfolding analysis of a first data set resulted in a two-dimensional representation which clearly reveals temporal regulation patterns for the genes and a meaningful structure for the time points, while the analysis of a second data set showed the algorithm's ability to go beyond a mere identification of those genes that discriminate between different patient or tissue types. Conclusion Multidimensional unfolding offers a useful tool for preliminary explorations of microarray data: By relying on an easy-to-grasp low-dimensional geometric framework, relations among genes, among conditions and between genes and conditions are simultaneously represented in an accessible way which may reveal interesting patterns in the data. An additional advantage of the method is that it can be applied to the raw data without necessitating the choice of suitable genewise transformations of the data. PMID:17550582

Spatial organization of multi-enzyme biocatalytic cascades.

PubMed

Quin, M B; Wallin, K K; Zhang, G; Schmidt-Dannert, C

2017-05-23

Industrial biocatalysis is an economically attractive option for the production of valuable chemicals. Our repertoire of cheap building blocks and commodity target molecules is vastly enhanced by multi-enzyme biocatalytic cascades. In order to achieve suitable titers in complex novel biocatalytic schemes, spatial organization may become necessary to overcome barriers caused by slow or inhibited enzymes as well as instability of biocatalysts. A number of spatial organization strategies are currently available, which could be integrated in the design of complex cascades. These include fusion proteins, immobilization on solid supports, multi-dimensional scaffolding, and encapsulation within vessels. This review article highlights recent advances in cascade biocatalysis, discusses the role of spatial organization in reaction kinetics, and presents some of the currently employed strategies for spatial organization of multi-enzyme cascades.

Meta-modelling, visualization and emulation of multi-dimensional data for virtual production intelligence

NASA Astrophysics Data System (ADS)

Schulz, Wolfgang; Hermanns, Torsten; Al Khawli, Toufik

2017-07-01

Decision making for competitive production in high-wage countries is a daily challenge where rational and irrational methods are used. The design of decision making processes is an intriguing, discipline spanning science. However, there are gaps in understanding the impact of the known mathematical and procedural methods on the usage of rational choice theory. Following Benjamin Franklin's rule for decision making formulated in London 1772, he called "Prudential Algebra" with the meaning of prudential reasons, one of the major ingredients of Meta-Modelling can be identified finally leading to one algebraic value labelling the results (criteria settings) of alternative decisions (parameter settings). This work describes the advances in Meta-Modelling techniques applied to multi-dimensional and multi-criterial optimization by identifying the persistence level of the corresponding Morse-Smale Complex. Implementations for laser cutting and laser drilling are presented, including the generation of fast and frugal Meta-Models with controlled error based on mathematical model reduction Reduced Models are derived to avoid any unnecessary complexity. Both, model reduction and analysis of multi-dimensional parameter space are used to enable interactive communication between Discovery Finders and Invention Makers. Emulators and visualizations of a metamodel are introduced as components of Virtual Production Intelligence making applicable the methods of Scientific Design Thinking and getting the developer as well as the operator more skilled.

Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR

PubMed Central

Mobli, Mehdi; Hoch, Jeffrey C.

2017-01-01

Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain measurement of the impulse response (the free induction decay, FID) consisted of sampling the signal at a series of discrete intervals. For compatibility with the discrete Fourier transform (DFT), the intervals are kept uniform, and the Nyquist theorem dictates the largest value of the interval sufficient to avoid aliasing. With the proposal by Jeener of parametric sampling along an indirect time dimension, extension to multidimensional experiments employed the same sampling techniques used in one dimension, similarly subject to the Nyquist condition and suitable for processing via the discrete Fourier transform. The challenges of obtaining high-resolution spectral estimates from short data records using the DFT were already well understood, however. Despite techniques such as linear prediction extrapolation, the achievable resolution in the indirect dimensions is limited by practical constraints on measuring time. The advent of non-Fourier methods of spectrum analysis capable of processing nonuniformly sampled data has led to an explosion in the development of novel sampling strategies that avoid the limits on resolution and measurement time imposed by uniform sampling. The first part of this review discusses the many approaches to data sampling in multidimensional NMR, the second part highlights commonly used methods for signal processing of such data, and the review concludes with a discussion of other approaches to speeding up data acquisition in NMR. PMID:25456315

Similarity from multi-dimensional scaling: solving the accuracy and diversity dilemma in information filtering.

PubMed

Zeng, Wei; Zeng, An; Liu, Hao; Shang, Ming-Sheng; Zhang, Yi-Cheng

2014-01-01

Recommender systems are designed to assist individual users to navigate through the rapidly growing amount of information. One of the most successful recommendation techniques is the collaborative filtering, which has been extensively investigated and has already found wide applications in e-commerce. One of challenges in this algorithm is how to accurately quantify the similarities of user pairs and item pairs. In this paper, we employ the multidimensional scaling (MDS) method to measure the similarities between nodes in user-item bipartite networks. The MDS method can extract the essential similarity information from the networks by smoothing out noise, which provides a graphical display of the structure of the networks. With the similarity measured from MDS, we find that the item-based collaborative filtering algorithm can outperform the diffusion-based recommendation algorithms. Moreover, we show that this method tends to recommend unpopular items and increase the global diversification of the networks in long term.

Multi-dimensional coherent optical spectroscopy of semiconductor nanostructures: Collinear and non-collinear approaches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nardin, Gaël; Li, Hebin; Autry, Travis M.

2015-03-21

We review our recent work on multi-dimensional coherent optical spectroscopy (MDCS) of semiconductor nanostructures. Two approaches, appropriate for the study of semiconductor materials, are presented and compared. A first method is based on a non-collinear geometry, where the Four-Wave-Mixing (FWM) signal is detected in the form of a radiated optical field. This approach works for samples with translational symmetry, such as Quantum Wells (QWs) or large and dense ensembles of Quantum Dots (QDs). A second method detects the FWM in the form of a photocurrent in a collinear geometry. This second approach extends the horizon of MDCS to sub-diffraction nanostructures,more » such as single QDs, nanowires, or nanotubes, and small ensembles thereof. Examples of experimental results obtained on semiconductor QW structures are given for each method. In particular, it is shown how MDCS can assess coupling between excitons confined in separated QWs.« less

MUSTA fluxes for systems of conservation laws

NASA Astrophysics Data System (ADS)

Toro, E. F.; Titarev, V. A.

2006-08-01

This paper is about numerical fluxes for hyperbolic systems and we first present a numerical flux, called GFORCE, that is a weighted average of the Lax-Friedrichs and Lax-Wendroff fluxes. For the linear advection equation with constant coefficient, the new flux reduces identically to that of the Godunov first-order upwind method. Then we incorporate GFORCE in the framework of the MUSTA approach [E.F. Toro, Multi-Stage Predictor-Corrector Fluxes for Hyperbolic Equations. Technical Report NI03037-NPA, Isaac Newton Institute for Mathematical Sciences, University of Cambridge, UK, 17th June, 2003], resulting in a version that we call GMUSTA. For non-linear systems this gives results that are comparable to those of the Godunov method in conjunction with the exact Riemann solver or complete approximate Riemann solvers, noting however that in our approach, the solution of the Riemann problem in the conventional sense is avoided. Both the GFORCE and GMUSTA fluxes are extended to multi-dimensional non-linear systems in a straightforward unsplit manner, resulting in linearly stable schemes that have the same stability regions as the straightforward multi-dimensional extension of Godunov's method. The methods are applicable to general meshes. The schemes of this paper share with the family of centred methods the common properties of being simple and applicable to a large class of hyperbolic systems, but the schemes of this paper are distinctly more accurate. Finally, we proceed to the practical implementation of our numerical fluxes in the framework of high-order finite volume WENO methods for multi-dimensional non-linear hyperbolic systems. Numerical results are presented for the Euler equations and for the equations of magnetohydrodynamics.

Multidimensional poverty, household environment and short-term morbidity in India.

PubMed

Dehury, Bidyadhar; Mohanty, Sanjay K

2017-01-01

Using the unit data from the second round of the Indian Human Development Survey (IHDS-II), 2011-2012, which covered 42,152 households, this paper examines the association between multidimensional poverty, household environmental deprivation and short-term morbidities (fever, cough and diarrhoea) in India. Poverty is measured in a multidimensional framework that includes the dimensions of education, health and income, while household environmental deprivation is defined as lack of access to improved sanitation, drinking water and cooking fuel. A composite index combining multidimensional poverty and household environmental deprivation has been computed, and households are classified as follows: multidimensional poor and living in a poor household environment, multidimensional non-poor and living in a poor household environment, multidimensional poor and living in a good household environment and multidimensional non-poor and living in a good household environment. Results suggest that about 23% of the population belonging to multidimensional poor households and living in a poor household environment had experienced short-term morbidities in a reference period of 30 days compared to 20% of the population belonging to multidimensional non-poor households and living in a poor household environment, 19% of the population belonging to multidimensional poor households and living in a good household environment and 15% of the population belonging to multidimensional non-poor households and living in a good household environment. Controlling for socioeconomic covariates, the odds of short-term morbidity was 1.47 [CI 1.40-1.53] among the multidimensional poor and living in a poor household environment, 1.28 [CI 1.21-1.37] among the multidimensional non-poor and living in a poor household environment and 1.21 [CI 1.64-1.28] among the multidimensional poor and living in a good household environment compared to the multidimensional non-poor and living in a good household environment. Results are robust across states and hold good for each of the three morbidities: fever, cough and diarrhoea. This establishes that along with poverty, household environmental conditions have a significant bearing on short-term morbidities in India. Public investment in sanitation, drinking water and cooking fuel can reduce the morbidity and improve the health of the population.

Method and structure for skewed block-cyclic distribution of lower-dimensional data arrays in higher-dimensional processor grids

DOEpatents

Chatterjee, Siddhartha [Yorktown Heights, NY; Gunnels, John A [Brewster, NY

2011-11-08

A method and structure of distributing elements of an array of data in a computer memory to a specific processor of a multi-dimensional mesh of parallel processors includes designating a distribution of elements of at least a portion of the array to be executed by specific processors in the multi-dimensional mesh of parallel processors. The pattern of the designating includes a cyclical repetitive pattern of the parallel processor mesh, as modified to have a skew in at least one dimension so that both a row of data in the array and a column of data in the array map to respective contiguous groupings of the processors such that a dimension of the contiguous groupings is greater than one.

High-Order Semi-Discrete Central-Upwind Schemes for Multi-Dimensional Hamilton-Jacobi Equations

NASA Technical Reports Server (NTRS)

Bryson, Steve; Levy, Doron; Biegel, Bran R. (Technical Monitor)

2002-01-01

We present high-order semi-discrete central-upwind numerical schemes for approximating solutions of multi-dimensional Hamilton-Jacobi (HJ) equations. This scheme is based on the use of fifth-order central interpolants like those developed in [1], in fluxes presented in [3]. These interpolants use the weighted essentially nonoscillatory (WENO) approach to avoid spurious oscillations near singularities, and become "central-upwind" in the semi-discrete limit. This scheme provides numerical approximations whose error is as much as an order of magnitude smaller than those in previous WENO-based fifth-order methods [2, 1]. Thee results are discussed via examples in one, two and three dimensions. We also pregnant explicit N-dimensional formulas for the fluxes, discuss their monotonicity and tl!e connection between this method and that in [2].

The assessment of function. Part II: clinical perspective of a javelin thrower with low back and groin pain

PubMed Central

Reiman, Michael P; Manske, Robert C

2012-01-01

Assessment of an individual’s functional ability can be complex. This assessment should also be individualized and adaptable to changes in functional status. In the first article of this series, we operationally defined function, discussed the construct of function, examined the evidence as it relates to assessment methods of various aspects of function, and explored the multi-dimensional nature of the concept of function. In this case report, we aim to demonstrate the utilization of a multi-dimensional assessment method (functional performance testing) as it relates to a high-level athlete presenting with pain in the low back and groin. It is our intent to demonstrate how the clinician should continually adapt their assessment dependent on the current functional abilities of the patients. PMID:23633887

Multidimensional Raman spectroscopic signatures as a tool for forensic identification of body fluid traces: a review.

PubMed

Sikirzhytski, Vitali; Sikirzhytskaya, Aliaksandra; Lednev, Igor K

2011-11-01

The analysis of body fluid traces during forensic investigations is a critical step in determining the key details of a crime. Several confirmatory and presumptive biochemical tests are currently utilized. However, these tests are all destructive, and no single method can be used to analyze all body fluids. This review outlines recent progress in the development of a novel universal approach for the nondestructive, confirmatory identification of body fluid traces using Raman spectroscopy. The method is based on the use of multidimensional spectroscopic signatures of body fluids and accounts for the intrinsic heterogeneity of dry traces and donor variation. The results presented here demonstrate that Raman spectroscopy has potential for identifying traces of semen, blood, saliva, sweat, and vaginal fluid with high confidence.

Multidimensional Compressed Sensing MRI Using Tensor Decomposition-Based Sparsifying Transform

PubMed Central

Yu, Yeyang; Jin, Jin; Liu, Feng; Crozier, Stuart

2014-01-01

Compressed Sensing (CS) has been applied in dynamic Magnetic Resonance Imaging (MRI) to accelerate the data acquisition without noticeably degrading the spatial-temporal resolution. A suitable sparsity basis is one of the key components to successful CS applications. Conventionally, a multidimensional dataset in dynamic MRI is treated as a series of two-dimensional matrices, and then various matrix/vector transforms are used to explore the image sparsity. Traditional methods typically sparsify the spatial and temporal information independently. In this work, we propose a novel concept of tensor sparsity for the application of CS in dynamic MRI, and present the Higher-order Singular Value Decomposition (HOSVD) as a practical example. Applications presented in the three- and four-dimensional MRI data demonstrate that HOSVD simultaneously exploited the correlations within spatial and temporal dimensions. Validations based on cardiac datasets indicate that the proposed method achieved comparable reconstruction accuracy with the low-rank matrix recovery methods and, outperformed the conventional sparse recovery methods. PMID:24901331

Evaluation of the selection methods used in the exIWO algorithm based on the optimization of multidimensional functions

NASA Astrophysics Data System (ADS)

Kostrzewa, Daniel; Josiński, Henryk

2016-06-01

The expanded Invasive Weed Optimization algorithm (exIWO) is an optimization metaheuristic modelled on the original IWO version inspired by dynamic growth of weeds colony. The authors of the present paper have modified the exIWO algorithm introducing a set of both deterministic and non-deterministic strategies of individuals' selection. The goal of the project was to evaluate the modified exIWO by testing its usefulness for multidimensional numerical functions optimization. The optimized functions: Griewank, Rastrigin, and Rosenbrock are frequently used as benchmarks because of their characteristics.

Structural diversity: a multi-dimensional approach to assess recreational services in urban parks.

PubMed

Voigt, Annette; Kabisch, Nadja; Wurster, Daniel; Haase, Dagmar; Breuste, Jürgen

2014-05-01

Urban green spaces provide important recreational services for urban residents. In general, when park visitors enjoy "the green," they are in actuality appreciating a mix of biotic, abiotic, and man-made park infrastructure elements and qualities. We argue that these three dimensions of structural diversity have an influence on how people use and value urban parks. We present a straightforward approach for assessing urban parks that combines multi-dimensional landscape mapping and questionnaire surveys. We discuss the method as well the results from its application to differently sized parks in Berlin and Salzburg.

Analysis of the time structure of synchronization in multidimensional chaotic systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Makarenko, A. V., E-mail: avm.science@mail.ru

2015-05-15

A new approach is proposed to the integrated analysis of the time structure of synchronization of multidimensional chaotic systems. The method allows one to diagnose and quantitatively evaluate the intermittency characteristics during synchronization of chaotic oscillations in the T-synchronization mode. A system of two identical logistic mappings with unidirectional coupling that operate in the developed chaos regime is analyzed. It is shown that the widely used approach, in which only synchronization patterns are subjected to analysis while desynchronization areas are considered as a background signal and removed from analysis, should be regarded as methodologically incomplete.

Non-negative Tensor Factorization for Robust Exploratory Big-Data Analytics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alexandrov, Boian; Vesselinov, Velimir Valentinov; Djidjev, Hristo Nikolov

Currently, large multidimensional datasets are being accumulated in almost every field. Data are: (1) collected by distributed sensor networks in real-time all over the globe, (2) produced by large-scale experimental measurements or engineering activities, (3) generated by high-performance simulations, and (4) gathered by electronic communications and socialnetwork activities, etc. Simultaneous analysis of these ultra-large heterogeneous multidimensional datasets is often critical for scientific discoveries, decision-making, emergency response, and national and global security. The importance of such analyses mandates the development of the next-generation of robust machine learning (ML) methods and tools for bigdata exploratory analysis.

Multidimensional chromatography in food analysis.

PubMed

Herrero, Miguel; Ibáñez, Elena; Cifuentes, Alejandro; Bernal, Jose

2009-10-23

In this work, the main developments and applications of multidimensional chromatographic techniques in food analysis are reviewed. Different aspects related to the existing couplings involving chromatographic techniques are examined. These couplings include multidimensional GC, multidimensional LC, multidimensional SFC as well as all their possible combinations. Main advantages and drawbacks of each coupling are critically discussed and their key applications in food analysis described.

Multidimensional Riemann problem with self-similar internal structure - part III - a multidimensional analogue of the HLLI Riemann solver for conservative hyperbolic systems

NASA Astrophysics Data System (ADS)

Balsara, Dinshaw S.; Nkonga, Boniface

2017-10-01

Just as the quality of a one-dimensional approximate Riemann solver is improved by the inclusion of internal sub-structure, the quality of a multidimensional Riemann solver is also similarly improved. Such multidimensional Riemann problems arise when multiple states come together at the vertex of a mesh. The interaction of the resulting one-dimensional Riemann problems gives rise to a strongly-interacting state. We wish to endow this strongly-interacting state with physically-motivated sub-structure. The fastest way of endowing such sub-structure consists of making a multidimensional extension of the HLLI Riemann solver for hyperbolic conservation laws. Presenting such a multidimensional analogue of the HLLI Riemann solver with linear sub-structure for use on structured meshes is the goal of this work. The multidimensional MuSIC Riemann solver documented here is universal in the sense that it can be applied to any hyperbolic conservation law. The multidimensional Riemann solver is made to be consistent with constraints that emerge naturally from the Galerkin projection of the self-similar states within the wave model. When the full eigenstructure in both directions is used in the present Riemann solver, it becomes a complete Riemann solver in a multidimensional sense. I.e., all the intermediate waves are represented in the multidimensional wave model. The work also presents, for the very first time, an important analysis of the dissipation characteristics of multidimensional Riemann solvers. The present Riemann solver results in the most efficient implementation of a multidimensional Riemann solver with sub-structure. Because it preserves stationary linearly degenerate waves, it might also help with well-balancing. Implementation-related details are presented in pointwise fashion for the one-dimensional HLLI Riemann solver as well as the multidimensional MuSIC Riemann solver.

A Sensitive and Robust Enzyme Kinetic Experiment Using Microplates and Fluorogenic Ester Substrates

ERIC Educational Resources Information Center

Johnson, R. Jeremy; Hoops, Geoffrey C.; Savas, Christopher J.; Kartje, Zachary; Lavis, Luke D.

2015-01-01

Enzyme kinetics measurements are a standard component of undergraduate biochemistry laboratories. The combination of serine hydrolases and fluorogenic enzyme substrates provides a rapid, sensitive, and general method for measuring enzyme kinetics in an undergraduate biochemistry laboratory. In this method, the kinetic activity of multiple protein…

Measuring Sexual Orientation: A Review and Critique of U.S. Data Collection Efforts and Implications for Health Policy.

PubMed

Wolff, Margaret; Wells, Brooke; Ventura-DiPersia, Christina; Renson, Audrey; Grov, Christian

The U.S. Department of Health and Human Services' (HHS) Healthy People 2020 goals sought to improve health outcomes among sexual minorities; HHS acknowledged that a dearth of sexual orientation items in federal and state health surveys obscured a broad understanding of sexual minority-related health disparities. The HHS 2011 data progression plan aimed to advance sexual orientation data collection efforts at the national level. Sexual orientation is a complex, multidimensional construct often composed of sexual identity, sexual attraction, and sexual behavior, thus posing challenges to its quantitative and practical measurement and analysis. In this review, we (a) present existing sexual orientation constructs; (b) evaluate current HHS sexual orientation data collection efforts; (c) review post-2011 data progression plan research on sexual minority health disparities, drawing on HHS survey data; (d) highlight the importance of and (e) identify obstacles to multidimensional sexual orientation measurement and analysis; and (f) discuss methods for multidimensional sexual orientation analysis and propose a matrix for addressing discordance/branchedness within these analyses. Multidimensional sexual orientation data collection and analysis would elucidate sexual minority-related health disparities, guide related health policies, and enhance population-based estimates of sexual minority individuals to steer health care practices.

Single-indicator-based Multidimensional Sensing: Detection and Identification of Heavy Metal Ions and Understanding the Foundations from Experiment to Simulation

PubMed Central

Leng, Yumin; Qian, Sihua; Wang, Yuhui; Lu, Cheng; Ji, Xiaoxu; Lu, Zhiwen; Lin, Hengwei

2016-01-01

Multidimensional sensing offers advantages in accuracy, diversity and capability for the simultaneous detection and discrimination of multiple analytes, however, the previous reports usually require complicated synthesis/fabrication process and/or need a variety of techniques (or instruments) to acquire signals. Therefore, to take full advantages of this concept, simple designs are highly desirable. Herein, a novel concept is conceived to construct multidimensional sensing platforms based on a single indicator that has capability of showing diverse color/fluorescence responses with the addition of different analytes. Through extracting hidden information from these responses, such as red, green and blue (RGB) alterations, a triple-channel-based multidimensional sensing platform could consequently be fabricated, and the RGB alterations are further applicable to standard statistical methods. As a proof-of-concept study, a triple-channel sensing platform is fabricated solely using dithizone with assistance of cetyltrimethylammonium bromide (CTAB) for hyperchromicity and sensitization, which demonstrates superior capabilities in detection and identification of ten common heavy metal ions at their standard concentrations of wastewater-discharge of China. Moreover, this sensing platform exhibits promising applications in semi-quantitative and even quantitative analysis individuals of these heavy metal ions with high sensitivity as well. Finally, density functional theory calculations are performed to reveal the foundations for this analysis. PMID:27146105

A Demonstration of Optimal Apodization Determination for Proper Lateral Modulation

NASA Astrophysics Data System (ADS)

Sumi, Chikayoshi; Komiya, Yuichi; Uga, Shinya

2009-07-01

We have realized effective ultrasound (US) beamformings by the steering of plural beams and apodizations for B-mode imaging with a high lateral resolution and accurate measurement of tissue or blood displacement vector and/or strain tensor using the multidimensional cross-spectrum phase gradient method (MCSPGM), or multidimensional autocorrelation or Doppler methods (MAM and MDM) using multidimensional analytic signals. For instance, the coherent superposition of the steered beams performed in the lateral cosine modulation method (LCM) has a higher potential for realizing a more accurate measurement of a displacement vector than the synthesis of the displacement vector using the accurately measured axial displacements obtained by the multidimensional synthetic aperture method (MDSAM), multidirectional transmission method (MTM) or the use of plural US transducers. Originally, the apodization function to be used for realizing a designed point spread function (PSF) was obtained by the Fraunhofer approximation (FA). However, to obtain the best approximated, designed PSF in the least-squares sense, we proposed a linear optimization (LO) method. Furthermore, on the basis of the knowledge about the losts of US energy during the propagation, we have recently developed a nonlinear optimization (NLO) method, in which the feet of the main lobes in apodization function are properly truncated. Thus, NLO also allows the decrease in the number of channels or the confinement of the effective aperture. In this study, to gain insight into the ideal shape of the PSF, the accuracies of the two-dimensional (2D) displacement vector measurements were compared for typical PSFs with distinct lateral envelope shapes, particularly, in terms of full width at half maximum (FWHM) and the length of the feet, i.e., the Gaussian function, Hanning window and parabolic function. It was confirmed that a PSF having a wide FWHM and short feet was ideal. Such a PSF yielded an echo with a high signal-to-noise ratio (SNR), a large bandwidth and a large maximum spectrum of the center frequency. Moreover, for the three PSFs used, by calculating the PSFs using a typical transducer model and the apodization functions obtained by the respective LO and NLO methods and FA, we compare the approximation accuracies of the realized PSFs. NLO was effective for realizing such an ideal PSF. In addition, NLO allowed the significant decrease in the number of channels or the confinement of the effective aperture. Thus, in the comparisons of the three distinct PSFs, we obtain an appropriate apodization function. This study will assist the realization of the best lateral modulation.

On the precision of quasi steady state assumptions in stochastic dynamics

NASA Astrophysics Data System (ADS)

Agarwal, Animesh; Adams, Rhys; Castellani, Gastone C.; Shouval, Harel Z.

2012-07-01

Many biochemical networks have complex multidimensional dynamics and there is a long history of methods that have been used for dimensionality reduction for such reaction networks. Usually a deterministic mass action approach is used; however, in small volumes, there are significant fluctuations from the mean which the mass action approach cannot capture. In such cases stochastic simulation methods should be used. In this paper, we evaluate the applicability of one such dimensionality reduction method, the quasi-steady state approximation (QSSA) [L. Menten and M. Michaelis, "Die kinetik der invertinwirkung," Biochem. Z 49, 333369 (1913)] for dimensionality reduction in case of stochastic dynamics. First, the applicability of QSSA approach is evaluated for a canonical system of enzyme reactions. Application of QSSA to such a reaction system in a deterministic setting leads to Michaelis-Menten reduced kinetics which can be used to derive the equilibrium concentrations of the reaction species. In the case of stochastic simulations, however, the steady state is characterized by fluctuations around the mean equilibrium concentration. Our analysis shows that a QSSA based approach for dimensionality reduction captures well the mean of the distribution as obtained from a full dimensional simulation but fails to accurately capture the distribution around that mean. Moreover, the QSSA approximation is not unique. We have then extended the analysis to a simple bistable biochemical network model proposed to account for the stability of synaptic efficacies; the substrate of learning and memory [J. E. Lisman, "A mechanism of memory storage insensitive to molecular turnover: A bistable autophosphorylating kinase," Proc. Natl. Acad. Sci. U.S.A. 82, 3055-3057 (1985)], 10.1073/pnas.82.9.3055. Our analysis shows that a QSSA based dimensionality reduction method results in errors as big as two orders of magnitude in predicting the residence times in the two stable states.

Hierarchical folding free energy landscape of HP35 revealed by most probable path clustering.

PubMed

Jain, Abhinav; Stock, Gerhard

2014-07-17

Adopting extensive molecular dynamics simulations of villin headpiece protein (HP35) by Shaw and co-workers, a detailed theoretical analysis of the folding of HP35 is presented. The approach is based on the recently proposed most probable path algorithm which identifies the metastable states of the system, combined with dynamical coring of these states in order to obtain a consistent Markov state model. The method facilitates the construction of a dendrogram associated with the folding free-energy landscape of HP35, which reveals a hierarchical funnel structure and shows that the native state is rather a kinetic trap than a network hub. The energy landscape of HP35 consists of the entropic unfolded basin U, where the prestructuring of the protein takes place, the intermediate basin I, which is connected to U via the rate-limiting U → I transition state reflecting the formation of helix-1, and the native basin N, containing a state close to the NMR structure and a native-like state that exhibits enhanced fluctuations of helix-3. The model is in line with recent experimental observations that the intermediate and native states differ mostly in their dynamics (locked vs unlocked states). Employing dihedral angle principal component analysis, subdiffusive motion on a multidimensional free-energy surface is found.

A general description of detachment for multidimensional modelling of biofilms.

PubMed

Xavier, Joao de Bivar; Picioreanu, Cristian; van Loosdrecht, Mark C M

2005-09-20

A general method for describing biomass detachment in multidimensional biofilm modelling is introduced. Biomass losses from processes acting on the entire surface of the biofilm, such as erosion, are modelled using a continuous detachment speed function F(det). Discrete detachment events, i.e. sloughing, are implicitly derived from simulations. The method is flexible to allow F(det) to take several forms, including expressions dependent on any state variables such as the local biofilm density. This methodology for biomass detachment was integrated with multidimensional (2D and 3D) particle-based multispecies biofilm models by using a novel application of the level set method. Application of the method is illustrated by trends in the dynamics of biofilms structure and activity derived from simulations performed on a simple model considering uniform biomass (case study I) and a model discriminating biomass composition in heterotrophic active mass, extracellular polymeric substances (EPS) and inert mass (case study II). Results from case study I demonstrate the effect of applied detachment forces as a fundamental factor influencing steady-state biofilm activity and structure. Trends from experimental observations reported in literature were correctly described. For example, simulation results indicated that biomass sloughing is reduced when erosion forces are increased. Case study II illustrates the application of the detachment methodology to systems with non-uniform biomass composition. Simulations carried out at different bulk concentrations of substrate show changes in biofilm structure (in terms of shape, density and spatial distribution of biomass components) and activity (in terms of oxygen and substrate consumption) as a consequence of either oxygen-limited or substrate-limited growth. (c) 2005 Wiley Periodicals, Inc.

A Multidimensional B-Spline Correction for Accurate Modeling Sugar Puckering in QM/MM Simulations.

PubMed

Huang, Ming; Dissanayake, Thakshila; Kuechler, Erich; Radak, Brian K; Lee, Tai-Sung; Giese, Timothy J; York, Darrin M

2017-09-12

The computational efficiency of approximate quantum mechanical methods allows their use for the construction of multidimensional reaction free energy profiles. It has recently been demonstrated that quantum models based on the neglect of diatomic differential overlap (NNDO) approximation have difficulty modeling deoxyribose and ribose sugar ring puckers and thus limit their predictive value in the study of RNA and DNA systems. A method has been introduced in our previous work to improve the description of the sugar puckering conformational landscape that uses a multidimensional B-spline correction map (BMAP correction) for systems involving intrinsically coupled torsion angles. This method greatly improved the adiabatic potential energy surface profiles of DNA and RNA sugar rings relative to high-level ab initio methods even for highly problematic NDDO-based models. In the present work, a BMAP correction is developed, implemented, and tested in molecular dynamics simulations using the AM1/d-PhoT semiempirical Hamiltonian for biological phosphoryl transfer reactions. Results are presented for gas-phase adiabatic potential energy surfaces of RNA transesterification model reactions and condensed-phase QM/MM free energy surfaces for nonenzymatic and RNase A-catalyzed transesterification reactions. The results show that the BMAP correction is stable, efficient, and leads to improvement in both the potential energy and free energy profiles for the reactions studied, as compared with ab initio and experimental reference data. Exploration of the effect of the size of the quantum mechanical region indicates the best agreement with experimental reaction barriers occurs when the full CpA dinucleotide substrate is treated quantum mechanically with the sugar pucker correction.

Combustor kinetic energy efficiency analysis of the hypersonic research engine data

NASA Astrophysics Data System (ADS)

Hoose, K. V.

1993-11-01

A one-dimensional method for measuring combustor performance is needed to facilitate design and development scramjet engines. A one-dimensional kinetic energy efficiency method is used for measuring inlet and nozzle performance. The objective of this investigation was to assess the use of kinetic energy efficiency as an indicator for scramjet combustor performance. A combustor kinetic energy efficiency analysis was performed on the Hypersonic Research Engine (HRE) data. The HRE data was chosen for this analysis due to its thorough documentation and availability. The combustor, inlet, and nozzle kinetic energy efficiency values were utilized to determine an overall engine kinetic energy efficiency. Finally, a kinetic energy effectiveness method was developed to eliminate thermochemical losses from the combustion of fuel and air. All calculated values exhibit consistency over the flight speed range. Effects from fuel injection, altitude, angle of attack, subsonic-supersonic combustion transition, and inlet spike position are shown and discussed. The results of analyzing the HRE data indicate that the kinetic energy efficiency method is effective as a measure of scramjet combustor performance.

Gradient-based multiconfiguration Shepard interpolation for generating potential energy surfaces for polyatomic reactions.

PubMed

Tishchenko, Oksana; Truhlar, Donald G

2010-02-28

This paper describes and illustrates a way to construct multidimensional representations of reactive potential energy surfaces (PESs) by a multiconfiguration Shepard interpolation (MCSI) method based only on gradient information, that is, without using any Hessian information from electronic structure calculations. MCSI, which is called multiconfiguration molecular mechanics (MCMM) in previous articles, is a semiautomated method designed for constructing full-dimensional PESs for subsequent dynamics calculations (classical trajectories, full quantum dynamics, or variational transition state theory with multidimensional tunneling). The MCSI method is based on Shepard interpolation of Taylor series expansions of the coupling term of a 2 x 2 electronically diabatic Hamiltonian matrix with the diagonal elements representing nonreactive analytical PESs for reactants and products. In contrast to the previously developed method, these expansions are truncated in the present version at the first order, and, therefore, no input of electronic structure Hessians is required. The accuracy of the interpolated energies is evaluated for two test reactions, namely, the reaction OH+H(2)-->H(2)O+H and the hydrogen atom abstraction from a model of alpha-tocopherol by methyl radical. The latter reaction involves 38 atoms and a 108-dimensional PES. The mean unsigned errors averaged over a wide range of representative nuclear configurations (corresponding to an energy range of 19.5 kcal/mol in the former case and 32 kcal/mol in the latter) are found to be within 1 kcal/mol for both reactions, based on 13 gradients in one case and 11 in the other. The gradient-based MCMM method can be applied for efficient representations of multidimensional PESs in cases where analytical electronic structure Hessians are too expensive or unavailable, and it provides new opportunities to employ high-level electronic structure calculations for dynamics at an affordable cost.

Column-coupling strategies for multidimensional electrophoretic separation techniques.

PubMed

Kler, Pablo A; Sydes, Daniel; Huhn, Carolin

2015-01-01

Multidimensional electrophoretic separations represent one of the most common strategies for dealing with the analysis of complex samples. In recent years we have been witnessing the explosive growth of separation techniques for the analysis of complex samples in applications ranging from life sciences to industry. In this sense, electrophoretic separations offer several strategic advantages such as excellent separation efficiency, different methods with a broad range of separation mechanisms, and low liquid consumption generating less waste effluents and lower costs per analysis, among others. Despite their impressive separation efficiency, multidimensional electrophoretic separations present some drawbacks that have delayed their extensive use: the volumes of the columns, and consequently of the injected sample, are significantly smaller compared to other analytical techniques, thus the coupling interfaces between two separations components must be very efficient in terms of providing geometrical precision with low dead volume. Likewise, very sensitive detection systems are required. Additionally, in electrophoretic separation techniques, the surface properties of the columns play a fundamental role for electroosmosis as well as the unwanted adsorption of proteins or other complex biomolecules. In this sense the requirements for an efficient coupling for electrophoretic separation techniques involve several aspects related to microfluidics and physicochemical interactions of the electrolyte solutions and the solid capillary walls. It is interesting to see how these multidimensional electrophoretic separation techniques have been used jointly with different detection techniques, for intermediate detection as well as for final identification and quantification, particularly important in the case of mass spectrometry. In this work we present a critical review about the different strategies for coupling two or more electrophoretic separation techniques and the different intermediate and final detection methods implemented for such separations.

The INTERGROWTH-21st Project Neurodevelopment Package: A Novel Method for the Multi-Dimensional Assessment of Neurodevelopment in Pre-School Age Children

PubMed Central

Fernandes, Michelle; Stein, Alan; Newton, Charles R.; Cheikh-Ismail, Leila; Kihara, Michael; Wulff, Katharina; de León Quintana, Enrique; Aranzeta, Luis; Soria-Frisch, Aureli; Acedo, Javier; Ibanez, David; Abubakar, Amina; Giuliani, Francesca; Lewis, Tamsin; Kennedy, Stephen; Villar, Jose

2014-01-01

Background The International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st) Project is a population-based, longitudinal study describing early growth and development in an optimally healthy cohort of 4607 mothers and newborns. At 24 months, children are assessed for neurodevelopmental outcomes with the INTERGROWTH-21st Neurodevelopment Package. This paper describes neurodevelopment tools for preschoolers and the systematic approach leading to the development of the Package. Methods An advisory panel shortlisted project-specific criteria (such as multi-dimensional assessments and suitability for international populations) to be fulfilled by a neurodevelopment instrument. A literature review of well-established tools for preschoolers revealed 47 candidates, none of which fulfilled all the project's criteria. A multi-dimensional assessment was, therefore, compiled using a package-based approach by: (i) categorizing desired outcomes into domains, (ii) devising domain-specific criteria for tool selection, and (iii) selecting the most appropriate measure for each domain. Results The Package measures vision (Cardiff tests); cortical auditory processing (auditory evoked potentials to a novelty oddball paradigm); and cognition, language skills, behavior, motor skills and attention (the INTERGROWTH-21st Neurodevelopment Assessment) in 35–45 minutes. Sleep-wake patterns (actigraphy) are also assessed. Tablet-based applications with integrated quality checks and automated, wireless electroencephalography make the Package easy to administer in the field by non-specialist staff. The Package is in use in Brazil, India, Italy, Kenya and the United Kingdom. Conclusions The INTERGROWTH-21st Neurodevelopment Package is a multi-dimensional instrument measuring early child development (ECD). Its developmental approach may be useful to those involved in large-scale ECD research and surveillance efforts. PMID:25423589

Range of sound levels in the outdoor environment

Treesearch

Lewis S. Goodfriend

1977-01-01

Current methods of measuring and rating noise in a metropolitan area are examined, including real-time spectrum analysis and sound-level integration, producing a single-number value representing the noise impact for each hour or each day. Methods of noise rating for metropolitan areas are reviewed, and the various measures from multidimensional rating methods such as...

Numerical Methods for 2-Dimensional Modeling

DTIC Science & Technology

1980-12-01

high-order finite element methods, and a multidimensional version of the method of lines, both utilizing an optimized stiff integrator for the time...integration. The finite element methods have proved disappointing, but the method of lines has provided an unexpectedly large gain in speed. Two...diffusion problems with the same number of unknowns (a 21 x 41 grid), solved by second-order finite element methods, took over seven minutes on the Cray-i

Automated Transition State Theory Calculations for High-Throughput Kinetics.

PubMed

Bhoorasingh, Pierre L; Slakman, Belinda L; Seyedzadeh Khanshan, Fariba; Cain, Jason Y; West, Richard H

2017-09-21

A scarcity of known chemical kinetic parameters leads to the use of many reaction rate estimates, which are not always sufficiently accurate, in the construction of detailed kinetic models. To reduce the reliance on these estimates and improve the accuracy of predictive kinetic models, we have developed a high-throughput, fully automated, reaction rate calculation method, AutoTST. The algorithm integrates automated saddle-point geometry search methods and a canonical transition state theory kinetics calculator. The automatically calculated reaction rates compare favorably to existing estimated rates. Comparison against high level theoretical calculations show the new automated method performs better than rate estimates when the estimate is made by a poor analogy. The method will improve by accounting for internal rotor contributions and by improving methods to determine molecular symmetry.

GLO-Roots: an imaging platform enabling multidimensional characterization of soil-grown root systems

PubMed Central

Rellán-Álvarez, Rubén; Lobet, Guillaume; Lindner, Heike; Pradier, Pierre-Luc; Sebastian, Jose; Yee, Muh-Ching; Geng, Yu; Trontin, Charlotte; LaRue, Therese; Schrager-Lavelle, Amanda; Haney, Cara H; Nieu, Rita; Maloof, Julin; Vogel, John P; Dinneny, José R

2015-01-01

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow the spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes. DOI: http://dx.doi.org/10.7554/eLife.07597.001 PMID:26287479

Tau lepton production and decays: perspective of multi-dimensional distributions and Monte Carlo methods

NASA Astrophysics Data System (ADS)

Was, Z.

2017-06-01

Status of τ lepton decay Monte Carlo generator TAUOLA, its main applications and recent developments are reviewed. It is underlined, that in recent efforts on development of new hadronic currents, the multi-dimensional nature of distributions of the experimental data must be taken with a great care: lesson from comparison and fits to the BaBar and Belle data is recalled. It was found, that as in the past at a time of comparisons with CLEO and ALEPH data, proper fitting, to as detailed as possible representation of the experimental data, is essential for appropriate developments of models of τ decay dynamic. This multi-dimensional nature of distributions is also important for observables where τ leptons are used to constrain experimental data. In later part of the presentation, use of the TAUOLA program for phenomenology of W, Z, H decays at LHC is addressed, in particular in the context of the Higgs boson parity measurements. Some new results, relevant for QED lepton pair emission are mentioned as well.

GLO-Roots: An imaging platform enabling multidimensional characterization of soil-grown root systems

DOE PAGES

Rellan-Alvarez, Ruben; Lobet, Guillaume; Lindner, Heike; ...

2015-08-19

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow themore » spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes.« less

Reciprocal effects between academic self-concept, self-esteem, achievement, and attainment over seven adolescent years: unidimensional and multidimensional perspectives of self-concept.

PubMed

Marsh, Herbert W; O'Mara, Alison

2008-04-01

In their influential review, Baumeister, Campbell, Krueger, and Vohs (2003) concluded that self-esteem--the global component of self-concept--has no effect on subsequent academic performance. In contrast, Marsh and Craven's (2006) review of reciprocal effects models from an explicitly multidimensional perspective demonstrated that academic self-concept and achievement are both a cause and an effect of each other. Ironically, both reviews cited classic Youth in Transition studies in support of their respective claims. In definitive tests of these counter claims, the authors reanalyze these data-including self-esteem (emphasized by Baumeister et al.), academic self-concept (emphasized by Marsh & Craven), and postsecondary educational attainment-using stronger statistical methods based on five waves of data (grade 10 through 5 years after graduation; N=2,213). Integrating apparently discrepant findings under a common theoretical framework based on a multidimensional perspective, academic self-concept had consistent reciprocal effects with both achievement and educational attainment, whereas self-esteem had almost none.

The scheme and research of TV series multidimensional comprehensive evaluation on cross-platform

NASA Astrophysics Data System (ADS)

Chai, Jianping; Bai, Xuesong; Zhou, Hongjun; Yin, Fulian

2016-10-01

As for shortcomings of the comprehensive evaluation system on traditional TV programs such as single data source, ignorance of new media as well as the high time cost and difficulty of making surveys, a new evaluation of TV series is proposed in this paper, which has a perspective in cross-platform multidimensional evaluation after broadcasting. This scheme considers the data directly collected from cable television and the Internet as research objects. It's based on TOPSIS principle, after preprocessing and calculation of the data, they become primary indicators that reflect different profiles of the viewing of TV series. Then after the process of reasonable empowerment and summation by the six methods(PCA, AHP, etc.), the primary indicators form the composite indices on different channels or websites. The scheme avoids the inefficiency and difficulty of survey and marking; At the same time, it not only reflects different dimensions of viewing, but also combines TV media and new media, completing the multidimensional comprehensive evaluation of TV series on cross-platform.

VTST/MT studies of the catalytic mechanism of C-H activation by transition metal complexes with [Cu2(μ-O2)], [Fe2(μ-O2)] and Fe(IV)-O cores based on DFT potential energy surfaces.

PubMed

Kim, Yongho; Mai, Binh Khanh; Park, Sumin

2017-04-01

High-valent Cu and Fe species, which are generated from dioxygen activation in metalloenzymes, carry out the functionalization of strong C-H bonds. Understanding the atomic details of the catalytic mechanism has long been one of the main objectives of bioinorganic chemistry. Large H/D kinetic isotope effects (KIEs) were observed in the C-H activation by high-valent non-heme Cu or Fe complexes in enzymes and their synthetic models. The H/D KIE depends significantly on the transition state properties, such as structure, energies, frequencies, and shape of the potential energy surface, when the tunneling effect is large. Therefore, theoretical predictions of kinetic parameters such as rate constants and KIEs can provide a reliable link between atomic-level quantum mechanical mechanisms and experiments. The accurate prediction of the tunneling effect is essential to reproduce the kinetic parameters. The rate constants and HD/KIE have been calculated using the variational transition-state theory including multidimensional tunneling based on DFT potential energy surfaces along the reaction coordinate. Excellent agreement was observed between the predicted and experimental results, which assures the validity of the DFT potential energy surfaces and, therefore, the proposed atomic-level mechanisms. The [Cu 2 (μ-O) 2 ], [Fe 2 (μ-O) 2 ], and Fe(IV)-oxo species were employed for C-H activation, and their role as catalysts was discussed at an atomic level.

Visualizing Mixed Variable-Type Multidimensional Data Using Tree Distances

DTIC Science & Technology

2015-09-01

24 1. The Regression Method .................................................. 25 2. Maximum Deviance Ratio Method... Deviance Change as a Factor of the Amount of Correlation? ................................................... 50 B. A PROPOSED SOLUTION...Splice mapping using d1 ...................... 36 Figure 18. Reduction in 2R analog ( deviance ratio-DevRat) per variable for the Splice data

Comparative kinetic analysis on thermal degradation of some cephalosporins using TG and DSC data

PubMed Central

2013-01-01

Background The thermal decomposition of cephalexine, cefadroxil and cefoperazone under non-isothermal conditions using the TG, respectively DSC methods, was studied. In case of TG, a hyphenated technique, including EGA, was used. Results The kinetic analysis was performed using the TG and DSC data in air for the first step of cephalosporin’s decomposition at four heating rates. The both TG and DSC data were processed according to an appropriate strategy to the following kinetic methods: Kissinger-Akahira-Sunose, Friedman, and NPK, in order to obtain realistic kinetic parameters, even if the decomposition process is a complex one. The EGA data offer some valuable indications about a possible decomposition mechanism. The obtained data indicate a rather good agreement between the activation energy’s values obtained by different methods, whereas the EGA data and the chemical structures give a possible explanation of the observed differences on the thermal stability. A complete kinetic analysis needs a data processing strategy using two or more methods, but the kinetic methods must also be applied to the different types of experimental data (TG and DSC). Conclusion The simultaneous use of DSC and TG data for the kinetic analysis coupled with evolved gas analysis (EGA) provided us a more complete picture of the degradation of the three cephalosporins. It was possible to estimate kinetic parameters by using three different kinetic methods and this allowed us to compare the Ea values obtained from different experimental data, TG and DSC. The thermodegradation being a complex process, the both differential and integral methods based on the single step hypothesis are inadequate for obtaining believable kinetic parameters. Only the modified NPK method allowed an objective separation of the temperature, respective conversion influence on the reaction rate and in the same time to ascertain the existence of two simultaneous steps. PMID:23594763

Fast and high-order numerical algorithms for the solution of multidimensional nonlinear fractional Ginzburg-Landau equation

NASA Astrophysics Data System (ADS)

Mohebbi, Akbar

2018-02-01

In this paper we propose two fast and accurate numerical methods for the solution of multidimensional space fractional Ginzburg-Landau equation (FGLE). In the presented methods, to avoid solving a nonlinear system of algebraic equations and to increase the accuracy and efficiency of method, we split the complex problem into simpler sub-problems using the split-step idea. For a homogeneous FGLE, we propose a method which has fourth-order of accuracy in time component and spectral accuracy in space variable and for nonhomogeneous one, we introduce another scheme based on the Crank-Nicolson approach which has second-order of accuracy in time variable. Due to using the Fourier spectral method for fractional Laplacian operator, the resulting schemes are fully diagonal and easy to code. Numerical results are reported in terms of accuracy, computational order and CPU time to demonstrate the accuracy and efficiency of the proposed methods and to compare the results with the analytical solutions. The results show that the present methods are accurate and require low CPU time. It is illustrated that the numerical results are in good agreement with the theoretical ones.

Efficient multidimensional free energy calculations for ab initio molecular dynamics using classical bias potentials

NASA Astrophysics Data System (ADS)

VandeVondele, Joost; Rothlisberger, Ursula

2000-09-01

We present a method for calculating multidimensional free energy surfaces within the limited time scale of a first-principles molecular dynamics scheme. The sampling efficiency is enhanced using selected terms of a classical force field as a bias potential. This simple procedure yields a very substantial increase in sampling accuracy while retaining the high quality of the underlying ab initio potential surface and can thus be used for a parameter free calculation of free energy surfaces. The success of the method is demonstrated by the applications to two gas phase molecules, ethane and peroxynitrous acid, as test case systems. A statistical analysis of the results shows that the entire free energy landscape is well converged within a 40 ps simulation at 500 K, even for a system with barriers as high as 15 kcal/mol.

Brain's tumor image processing using shearlet transform

NASA Astrophysics Data System (ADS)

Cadena, Luis; Espinosa, Nikolai; Cadena, Franklin; Korneeva, Anna; Kruglyakov, Alexey; Legalov, Alexander; Romanenko, Alexey; Zotin, Alexander

2017-09-01

Brain tumor detection is well known research area for medical and computer scientists. In last decades there has been much research done on tumor detection, segmentation, and classification. Medical imaging plays a central role in the diagnosis of brain tumors and nowadays uses methods non-invasive, high-resolution techniques, especially magnetic resonance imaging and computed tomography scans. Edge detection is a fundamental tool in image processing, particularly in the areas of feature detection and feature extraction, which aim at identifying points in a digital image at which the image has discontinuities. Shearlets is the most successful frameworks for the efficient representation of multidimensional data, capturing edges and other anisotropic features which frequently dominate multidimensional phenomena. The paper proposes an improved brain tumor detection method by automatically detecting tumor location in MR images, its features are extracted by new shearlet transform.

Reasons for leaving nursing: a study among Turkish nurses.

PubMed

Gök, Ayşen Uğur; Kocaman, Gülseren

2011-08-01

Reasons for the growing nursing shortage are often complex and multidimensional. To explore the phenomenon of why Turkish nurses leave nursing. The sample in this descriptive study was 134 nurses who had left the profession. A snowball sampling method was used to identify subjects and multiple methods were used to elicit reasons for leaving. Data analysis included descriptive statistics. The main reasons for leaving nursing were related to unsatisfactory working conditions and a negative perception of nursing. Of the respondents, 69.4% received education in a non-nursing field. The most popular career choice was teaching (27.6%). The results of this study indicate that working conditions and public opinion adversely affect a nurse's interest in the profession. The results of the study indicate a need to improve working conditions and to approach this subject from a multidimensional perspective.

Deadlock-free class routes for collective communications embedded in a multi-dimensional torus network

DOEpatents

Chen, Dong; Eisley, Noel A.; Steinmacher-Burow, Burkhard; Heidelberger, Philip

2013-01-29

A computer implemented method and a system for routing data packets in a multi-dimensional computer network. The method comprises routing a data packet among nodes along one dimension towards a root node, each node having input and output communication links, said root node not having any outgoing uplinks, and determining at each node if the data packet has reached a predefined coordinate for the dimension or an edge of the subrectangle for the dimension, and if the data packet has reached the predefined coordinate for the dimension or the edge of the subrectangle for the dimension, determining if the data packet has reached the root node, and if the data packet has not reached the root node, routing the data packet among nodes along another dimension towards the root node.

Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR.

PubMed

Mobli, Mehdi; Hoch, Jeffrey C

2014-11-01

Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain measurement of the impulse response (the free induction decay, FID) consisted of sampling the signal at a series of discrete intervals. For compatibility with the discrete Fourier transform (DFT), the intervals are kept uniform, and the Nyquist theorem dictates the largest value of the interval sufficient to avoid aliasing. With the proposal by Jeener of parametric sampling along an indirect time dimension, extension to multidimensional experiments employed the same sampling techniques used in one dimension, similarly subject to the Nyquist condition and suitable for processing via the discrete Fourier transform. The challenges of obtaining high-resolution spectral estimates from short data records using the DFT were already well understood, however. Despite techniques such as linear prediction extrapolation, the achievable resolution in the indirect dimensions is limited by practical constraints on measuring time. The advent of non-Fourier methods of spectrum analysis capable of processing nonuniformly sampled data has led to an explosion in the development of novel sampling strategies that avoid the limits on resolution and measurement time imposed by uniform sampling. The first part of this review discusses the many approaches to data sampling in multidimensional NMR, the second part highlights commonly used methods for signal processing of such data, and the review concludes with a discussion of other approaches to speeding up data acquisition in NMR. Copyright © 2014 Elsevier B.V. All rights reserved.

A reduced basis approach for implementing thermodynamic phase-equilibria information in geophysical and geodynamic studies

NASA Astrophysics Data System (ADS)

Afonso, J. C.; Zlotnik, S.; Diez, P.

2015-12-01

We present a flexible, general and efficient approach for implementing thermodynamic phase equilibria information (in the form of sets of physical parameters) into geophysical and geodynamic studies. The approach is based on multi-dimensional decomposition methods, which transform the original multi-dimensional discrete information into a dimensional-separated representation. This representation has the property of increasing the number of coefficients to be stored linearly with the number of dimensions (opposite to a full multi-dimensional cube requiring exponential storage depending on the number of dimensions). Thus, the amount of information to be stored in memory during a numerical simulation or geophysical inversion is drastically reduced. Accordingly, the amount and resolution of the thermodynamic information that can be used in a simulation or inversion increases substantially. In addition, the method is independent of the actual software used to obtain the primary thermodynamic information, and therefore it can be used in conjunction with any thermodynamic modeling program and/or database. Also, the errors associated with the decomposition procedure are readily controlled by the user, depending on her/his actual needs (e.g. preliminary runs vs full resolution runs). We illustrate the benefits, generality and applicability of our approach with several examples of practical interest for both geodynamic modeling and geophysical inversion/modeling. Our results demonstrate that the proposed method is a competitive and attractive candidate for implementing thermodynamic constraints into a broad range of geophysical and geodynamic studies.

Multi-dimensional, fully implicit, exactly conserving electromagnetic particle-in-cell simulations in curvilinear geometry

NASA Astrophysics Data System (ADS)

Chen, Guangye; Chacon, Luis

2015-11-01

We discuss a new, conservative, fully implicit 2D3V Vlasov-Darwin particle-in-cell algorithm in curvilinear geometry for non-radiative, electromagnetic kinetic plasma simulations. Unlike standard explicit PIC schemes, fully implicit PIC algorithms are unconditionally stable and allow exact discrete energy and charge conservation. Here, we extend these algorithms to curvilinear geometry. The algorithm retains its exact conservation properties in curvilinear grids. The nonlinear iteration is effectively accelerated with a fluid preconditioner for weakly to modestly magnetized plasmas, which allows efficient use of large timesteps, O (√{mi/me}c/veT) larger than the explicit CFL. In this presentation, we will introduce the main algorithmic components of the approach, and demonstrate the accuracy and efficiency properties of the algorithm with various numerical experiments in 1D (slow shock) and 2D (island coalescense).

Numeric invariants from multidimensional persistence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skryzalin, Jacek; Carlsson, Gunnar

2017-05-19

In this paper, we analyze the space of multidimensional persistence modules from the perspectives of algebraic geometry. We first build a moduli space of a certain subclass of easily analyzed multidimensional persistence modules, which we construct specifically to capture much of the information which can be gained by using multidimensional persistence over one-dimensional persistence. We argue that the global sections of this space provide interesting numeric invariants when evaluated against our subclass of multidimensional persistence modules. Lastly, we extend these global sections to the space of all multidimensional persistence modules and discuss how the resulting numeric invariants might be usedmore » to study data.« less

Computational study of the thermochemistry of N₂O₅ and the kinetics of the reaction N₂O₅ + H₂O → 2 HNO₃.

PubMed

Alecu, I M; Marshall, Paul

2014-12-04

The multistructural method for torsional anharmonicity (MS-T) is employed to compute anharmonic conformationally averaged partition functions which then serve as the basis for the calculation of thermochemical parameters for N2O5 over the temperature range 0-3000 K, and thermal rate constants for the hydrolysis reaction N2O5 + H2O → 2 HNO3 over the temperature range 180-1800 K. The M06-2X hybrid meta-GGA density functional paired with the MG3S basis set is used to compute the properties of all stationary points and the energies, gradients, and Hessians of nonstationary points along the reaction path, with further energy refinement at stationary points obtained via single-point CCSD(T)-F12a/cc-pVTZ-F12 calculations including corrections for core-valence and scalar relativistic effects. The internal rotations in dinitrogen pentoxide are found to generate three structures (conformations) whose contributions are included in the partition function via the MS-T formalism, leading to a computed value for S°(298.15)(N2O5) of 353.45 J mol(-1) K(-1).This new estimate for S°(298.15)(N2O5) is used to reanalyze the equilibrium constants for the reaction NO3 + NO2 = N2O5 measured by Osthoff et al. [Phys. Chem. Chem. Phys. 2007, 9, 5785-5793] to arrive at ΔfH °(298.15) (N2O5) = 14.31 ± 0.53 kJ mol(-1)via the third law method, which compares well with our computed ab initio value of 13.53 ± 0.56 kJ mol(-1). Finally, multistructural canonical variational-transition-state theory with multidimensional tunneling (MS-CVT/MT) is used to study the kinetics for hydrolysis of N2O5 by a single water molecule, whose rate constant can be summarized by the Arrhenius expression 9.51 × 10(-17) (T/298 K)(3.354) e(-7900K/T) cm3 molecule(-1) s(-1) over the temperature range 180-1800 K.

Foundations of modelling of nonequilibrium low-temperature plasmas

NASA Astrophysics Data System (ADS)

Alves, L. L.; Bogaerts, A.; Guerra, V.; Turner, M. M.

2018-02-01

This work explains the need for plasma models, introduces arguments for choosing the type of model that better fits the purpose of each study, and presents the basics of the most common nonequilibrium low-temperature plasma models and the information available from each one, along with an extensive list of references for complementary in-depth reading. The paper presents the following models, organised according to the level of multi-dimensional description of the plasma: kinetic models, based on either a statistical particle-in-cell/Monte-Carlo approach or the solution to the Boltzmann equation (in the latter case, special focus is given to the description of the electron kinetics); multi-fluid models, based on the solution to the hydrodynamic equations; global (spatially-average) models, based on the solution to the particle and energy rate-balance equations for the main plasma species, usually including a very complete reaction chemistry; mesoscopic models for plasma-surface interaction, adopting either a deterministic approach or a stochastic dynamical Monte-Carlo approach. For each plasma model, the paper puts forward the physics context, introduces the fundamental equations, presents advantages and limitations, also from a numerical perspective, and illustrates its application with some examples. Whenever pertinent, the interconnection between models is also discussed, in view of multi-scale hybrid approaches.

Experimental and Modeling Studies of the Combustion Characteristics of Conventional and Alternative Jet Fuels. Final Report

NASA Technical Reports Server (NTRS)

Meeks, Ellen; Naik, Chitral V.; Puduppakkam, Karthik V.; Modak, Abhijit; Egolfopoulos, Fokion N.; Tsotsis, Theo; Westbrook, Charles K.

2011-01-01

The objectives of this project have been to develop a comprehensive set of fundamental data regarding the combustion behavior of jet fuels and appropriately associated model fuels. Based on the fundamental study results, an auxiliary objective was to identify differentiating characteristics of molecular fuel components that can be used to explain different fuel behavior and that may ultimately be used in the planning and design of optimal fuel-production processes. The fuels studied in this project were Fischer-Tropsch (F-T) fuels and biomass-derived jet fuels that meet certain specifications of currently used jet propulsion applications. Prior to this project, there were no systematic experimental flame data available for such fuels. One of the key goals has been to generate such data, and to use this data in developing and verifying effective kinetic models. The models have then been reduced through automated means to enable multidimensional simulation of the combustion characteristics of such fuels in real combustors. Such reliable kinetic models, validated against fundamental data derived from laminar flames using idealized flow models, are key to the development and design of optimal combustors and fuels. The models provide direct information about the relative contribution of different molecular constituents to the fuel performance and can be used to assess both combustion and emissions characteristics.

Applying the Consensual Method of Estimating Poverty in a Low Income African Setting.

PubMed

Nandy, Shailen; Pomati, Marco

We present the first study of multidimensional poverty in Benin using the consensual or socially perceived necessities approach. There is a remarkable level consensus about what constitutes the necessities of life and an adequate standard of living. Following Townsend's concept of relative deprivation, we show how social consensus provides the basis for a reliable and valid index of multiple deprivation, which can be used to reflect multidimensional poverty. We discuss the issue of adaptive preferences, which has previously been used to criticise the consensual approach, and provide evidence to contest the claim that the poor adjust their aspirations downwards.

Framework for analyzing ecological trait-based models in multidimensional niche spaces

NASA Astrophysics Data System (ADS)

Biancalani, Tommaso; DeVille, Lee; Goldenfeld, Nigel

2015-05-01

We develop a theoretical framework for analyzing ecological models with a multidimensional niche space. Our approach relies on the fact that ecological niches are described by sequences of symbols, which allows us to include multiple phenotypic traits. Ecological drivers, such as competitive exclusion, are modeled by introducing the Hamming distance between two sequences. We show that a suitable transform diagonalizes the community interaction matrix of these models, making it possible to predict the conditions for niche differentiation and, close to the instability onset, the asymptotically long time population distributions of niches. We exemplify our method using the Lotka-Volterra equations with an exponential competition kernel.

Current Status on the use of Parallel Computing in Turbulent Reacting Flow Computations Involving Sprays, Monte Carlo PDF and Unstructured Grids. Chapter 4

NASA Technical Reports Server (NTRS)

Raju, M. S.

1998-01-01

The state of the art in multidimensional combustor modeling as evidenced by the level of sophistication employed in terms of modeling and numerical accuracy considerations, is also dictated by the available computer memory and turnaround times afforded by present-day computers. With the aim of advancing the current multi-dimensional computational tools used in the design of advanced technology combustors, a solution procedure is developed that combines the novelty of the coupled CFD/spray/scalar Monte Carlo PDF (Probability Density Function) computations on unstructured grids with the ability to run on parallel architectures. In this approach, the mean gas-phase velocity and turbulence fields are determined from a standard turbulence model, the joint composition of species and enthalpy from the solution of a modeled PDF transport equation, and a Lagrangian-based dilute spray model is used for the liquid-phase representation. The gas-turbine combustor flows are often characterized by a complex interaction between various physical processes associated with the interaction between the liquid and gas phases, droplet vaporization, turbulent mixing, heat release associated with chemical kinetics, radiative heat transfer associated with highly absorbing and radiating species, among others. The rate controlling processes often interact with each other at various disparate time 1 and length scales. In particular, turbulence plays an important role in determining the rates of mass and heat transfer, chemical reactions, and liquid phase evaporation in many practical combustion devices.

Best Design for Multidimensional Computerized Adaptive Testing with the Bifactor Model

ERIC Educational Resources Information Center

Seo, Dong Gi; Weiss, David J.

2015-01-01

Most computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm…

Multidimensional Measurement of Poverty among Women in Sub-Saharan Africa

ERIC Educational Resources Information Center

Batana, Yele Maweki

2013-01-01

Since the seminal work of Sen, poverty has been recognized as a multidimensional phenomenon. The recent availability of relevant databases renewed the interest in this approach. This paper estimates multidimensional poverty among women in fourteen Sub-Saharan African countries using the Alkire and Foster multidimensional poverty measures, whose…

Discussion of the Investigation Method on the Reaction Kinetics of Metallurgical Reaction Engineering

NASA Astrophysics Data System (ADS)

Du, Ruiling; Wu, Keng; Zhang, Jiazhi; Zhao, Yong

Reaction kinetics of metallurgical physical chemistry which was successfully applied in metallurgy (as ferrous metallurgy, non-ferrous metallurgy) became an important theoretical foundation for subject system of traditional metallurgy. Not only the research methods were very perfect, but also the independent structures and systems of it had been formed. One of the important tasks of metallurgical reaction engineering was the simulation of metallurgical process. And then, the mechanism of reaction process and the conversion time points of different control links should be obtained accurately. Therefore, the research methods and results of reaction kinetics in metallurgical physical chemistry were not very suitable for metallurgical reaction engineering. In order to provide the definite conditions of transmission, reaction kinetics parameters and the conversion time points of different control links for solving the transmission and reaction equations in metallurgical reaction engineering, a new method for researching kinetics mechanisms in metallurgical reaction engineering was proposed, which was named stepwise attempt method. Then the comparison of results between the two methods and the further development of stepwise attempt method were discussed in this paper. As a new research method for reaction kinetics in metallurgical reaction engineering, stepwise attempt method could not only satisfy the development of metallurgical reaction engineering, but also provide necessary guarantees for establishing its independent subject system.

A gas-kinetic BGK scheme for the compressible Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Xu, Kun

2000-01-01

This paper presents an improved gas-kinetic scheme based on the Bhatnagar-Gross-Krook (BGK) model for the compressible Navier-Stokes equations. The current method extends the previous gas-kinetic Navier-Stokes solver developed by Xu and Prendergast by implementing a general nonequilibrium state to represent the gas distribution function at the beginning of each time step. As a result, the requirement in the previous scheme, such as the particle collision time being less than the time step for the validity of the BGK Navier-Stokes solution, is removed. Therefore, the applicable regime of the current method is much enlarged and the Navier-Stokes solution can be obtained accurately regardless of the ratio between the collision time and the time step. The gas-kinetic Navier-Stokes solver developed by Chou and Baganoff is the limiting case of the current method, and it is valid only under such a limiting condition. Also, in this paper, the appropriate implementation of boundary condition for the kinetic scheme, different kinetic limiting cases, and the Prandtl number fix are presented. The connection among artificial dissipative central schemes, Godunov-type schemes, and the gas-kinetic BGK method is discussed. Many numerical tests are included to validate the current method.

METAGUI. A VMD interface for analyzing metadynamics and molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Biarnés, Xevi; Pietrucci, Fabio; Marinelli, Fabrizio; Laio, Alessandro

2012-01-01

We present a new computational tool, METAGUI, which extends the VMD program with a graphical user interface that allows constructing a thermodynamic and kinetic model of a given process simulated by large-scale molecular dynamics. The tool is specially designed for analyzing metadynamics based simulations. The huge amount of diverse structures generated during such a simulation is partitioned into a set of microstates (i.e. structures with similar values of the collective variables). Their relative free energies are then computed by a weighted-histogram procedure and the most relevant free energy wells are identified by diagonalization of the rate matrix followed by a commitor analysis. All this procedure leads to a convenient representation of the metastable states and long-time kinetics of the system which can be compared with experimental data. The tool allows to seamlessly switch between a collective variables space representation of microstates and their atomic structure representation, which greatly facilitates the set-up and analysis of molecular dynamics simulations. METAGUI is based on the output format of the PLUMED plugin, making it compatible with a number of different molecular dynamics packages like AMBER, NAMD, GROMACS and several others. The METAGUI source files can be downloaded from the PLUMED web site ( http://www.plumed-code.org). Program summaryProgram title: METAGUI Catalogue identifier: AEKH_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKH_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License version 3 No. of lines in distributed program, including test data, etc.: 117 545 No. of bytes in distributed program, including test data, etc.: 8 516 203 Distribution format: tar.gz Programming language: TK/TCL, Fortran Computer: Any computer with a VMD installation and capable of running an executable produced by a gfortran compiler Operating system: Linux, Unix OS-es RAM: 1 073 741 824 bytes Classification: 23 External routines: A VMD installation ( http://www.ks.uiuc.edu/Research/vmd/) Nature of problem: Extract thermodynamic data and build a kinetic model of a given process simulated by metadynamics or molecular dynamics simulations, and provide this information on a dual representation that allows navigating and exploring the molecular structures corresponding to each point along the multi-dimensional free energy hypersurface. Solution method: Graphical-user interface linked to VMD that clusterizes the simulation trajectories in the space of a set of collective variables and assigns each frame to a given microstate, determines the free energy of each microstate by a weighted histogram analysis method, and identifies the most relevant free energy wells (kinetic basins) by diagonalization of the rate matrix followed by a commitor analysis. Restrictions: Input format files compatible with PLUMED and all the MD engines supported by PLUMED and VMD. Running time: A few minutes.

COREPA-M: A MULTI-DIMENSIONAL FORMULATION OF COREPA

EPA Science Inventory

Recently, the COmmon REactivity PAttern (COREPA) approach was developed as a probabilistic classification method which was formalized specifically to advance mechanistic QSAR development by addressing the impact of molecular flexibility on stereoelectronic properties of chemicals...

A Visual Analytics Approach for Station-Based Air Quality Data

PubMed Central

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-01-01

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support. PMID:28029117

Successful aging as a multidimensional concept: An integrative review

PubMed Central

Zanjari, Nasibeh; Sharifian Sani, Maryam; Chavoshi, Meimanat Hosseini; Rafiey, Hassan; Mohammadi Shahboulaghi, Farahnaz

2017-01-01

Background: Successful aging as an umbrella term with a large amount of literature has emerged with a variety of meanings and dimensions in different studies. This article aims at determining what dimensions contribute to constructing the concept of successful aging. Methods: The method used in this study is an integrative review of published literature related to successful aging. This method includes both qualitative and quantitative studies. Data searching was conducted during November and December 2014 and was then updated in October 2015. First, 2543 articles were identified, and after the screening phase, 76 articles were eligible for inclusion in the integrative review. Results: The results specified 14 subcategories and 5 main categories of successful aging: social well-being, psychological wellbeing, physical health, spirituality and transcendence, and environment and economic security. Conclusion: The present study provides a thorough understanding of successful aging dimensions and proposes the importance of the multidimensional concept of successful aging at the individual, interpersonal, and environmental levels for future studies and policymaking on population aging.

Similarity from Multi-Dimensional Scaling: Solving the Accuracy and Diversity Dilemma in Information Filtering

PubMed Central

Zeng, Wei; Zeng, An; Liu, Hao; Shang, Ming-Sheng; Zhang, Yi-Cheng

2014-01-01

Recommender systems are designed to assist individual users to navigate through the rapidly growing amount of information. One of the most successful recommendation techniques is the collaborative filtering, which has been extensively investigated and has already found wide applications in e-commerce. One of challenges in this algorithm is how to accurately quantify the similarities of user pairs and item pairs. In this paper, we employ the multidimensional scaling (MDS) method to measure the similarities between nodes in user-item bipartite networks. The MDS method can extract the essential similarity information from the networks by smoothing out noise, which provides a graphical display of the structure of the networks. With the similarity measured from MDS, we find that the item-based collaborative filtering algorithm can outperform the diffusion-based recommendation algorithms. Moreover, we show that this method tends to recommend unpopular items and increase the global diversification of the networks in long term. PMID:25343243

A Visual Analytics Approach for Station-Based Air Quality Data.

PubMed

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-12-24

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support.

Data-driven Green's function retrieval and application to imaging with multidimensional deconvolution

NASA Astrophysics Data System (ADS)

Broggini, Filippo; Wapenaar, Kees; van der Neut, Joost; Snieder, Roel

2014-01-01

An iterative method is presented that allows one to retrieve the Green's function originating from a virtual source located inside a medium using reflection data measured only at the acquisition surface. In addition to the reflection response, an estimate of the travel times corresponding to the direct arrivals is required. However, no detailed information about the heterogeneities in the medium is needed. The iterative scheme generalizes the Marchenko equation for inverse scattering to the seismic reflection problem. To give insight in the mechanism of the iterative method, its steps for a simple layered medium are analyzed using physical arguments based on the stationary phase method. The retrieved Green's wavefield is shown to correctly contain the multiples due to the inhomogeneities present in the medium. Additionally, a variant of the iterative scheme enables decomposition of the retrieved wavefield into its downgoing and upgoing components. These wavefields then enable creation of a ghost-free image of the medium with either cross correlation or multidimensional deconvolution, presenting an advantage over standard prestack migration.

A Technique of Two-Stage Clustering Applied to Environmental and Civil Engineering and Related Methods of Citation Analysis.

ERIC Educational Resources Information Center

Miyamoto, S.; Nakayama, K.

1983-01-01

A method of two-stage clustering of literature based on citation frequency is applied to 5,065 articles from 57 journals in environmental and civil engineering. Results of related methods of citation analysis (hierarchical graph, clustering of journals, multidimensional scaling) applied to same set of articles are compared. Ten references are…

Scale Development and Initial Tests of the Multidimensional Complex Adaptive Leadership Scale for School Principals: An Exploratory Mixed Method Study

ERIC Educational Resources Information Center

Özen, Hamit; Turan, Selahattin

2017-01-01

This study was designed to develop the scale of the Complex Adaptive Leadership for School Principals (CAL-SP) and examine its psychometric properties. This was an exploratory mixed method research design (ES-MMD). Both qualitative and quantitative methods were used to develop and assess psychometric properties of the questionnaire. This study…

Experimental and Computational Study fo CH, CH*, and OH* in an Axisymmetric Laminar Diffusion Flame

NASA Technical Reports Server (NTRS)

Walsh, K. T.

1998-01-01

In this study, we extend the results of previous combined numerical and experimental investigations of an axisymmetric laminar diffusion flame in which difference Raman spectroscopy, laser-induced fluorescence (LIF), and a multidimensional flame model were used to generate profiles of the temperature and major and minor species. A procedure is outlined by which the number densities of ground-state CH (X(sup 2)II) excited-state CH (A(sup 2)Delta, denoted CH*), and excited-state OH (A(sup 2)Sigma, denoted OH*) are measured and modeled. CH* and OH* number densities are deconvoluted from line-of-sight flame-emission measurements. Ground-state CH is measured using linear LIF. The computations are done with GRI Mech 2.11 as well as an alternate hydrocarbon mechanism. In both cases, additional reactions for the production and consumption of CH* and OH* are added from recent kinetic studies. Collisional quenching and spontaneous emission are responsible for the de-excitation of the excited-state radicals. As with our previous investigations, GRI Mech 2.11 continues to produce very good agreement with the overall flame length observed in the experiments, while significantly under predicting the flame lift-off height. The alternate kinetic scheme is much more accurate in predicting lift-off height but overpredicts the over-all flame length. Ground-state CH profiles predicted with GRI Mech 2.11 are in excellent agreement with the corresponding measurements, regarding both spatial distribution and absolute concentration (measured at 4 ppm) of the CH radical. Calculations of the excited-state species show reasonable agreement with the measurements as far as spatial distribution and overall characteristics are concerned. For OH*, the measured peak mole fraction, 1.3 x 10(exp -8), compared well with computed peaks, while the measured peak level for CH*, 2 x 10(exp -9), was severely underpredicted by both kinetic schemes, indicating that the formation and destruction kinetics associated with excited-state species in flames require further research.

Methods for evaluating information in managing the enterprise on the basis of a hybrid three-tier system

NASA Astrophysics Data System (ADS)

Vasil'ev, V. A.; Dobrynina, N. V.

2017-01-01

The article presents data on the influence of information upon the functioning of complex systems in the process of ensuring their effective management. Ways and methods for evaluating multidimensional information that reduce time and resources, improve the validity of the studied system management decisions, were proposed.

The Robustness of IRT-Based Vertical Scaling Methods to Violation of Unidimensionality

ERIC Educational Resources Information Center

Yin, Liqun

2013-01-01

In recent years, many states have adopted Item Response Theory (IRT) based vertically scaled tests due to their compelling features in a growth-based accountability context. However, selection of a practical and effective calibration/scaling method and proper understanding of issues with possible multidimensionality in the test data is critical to…

ICM: a web server for integrated clustering of multi-dimensional biomedical data.

PubMed

He, Song; He, Haochen; Xu, Wenjian; Huang, Xin; Jiang, Shuai; Li, Fei; He, Fuchu; Bo, Xiaochen

2016-07-08

Large-scale efforts for parallel acquisition of multi-omics profiling continue to generate extensive amounts of multi-dimensional biomedical data. Thus, integrated clustering of multiple types of omics data is essential for developing individual-based treatments and precision medicine. However, while rapid progress has been made, methods for integrated clustering are lacking an intuitive web interface that facilitates the biomedical researchers without sufficient programming skills. Here, we present a web tool, named Integrated Clustering of Multi-dimensional biomedical data (ICM), that provides an interface from which to fuse, cluster and visualize multi-dimensional biomedical data and knowledge. With ICM, users can explore the heterogeneity of a disease or a biological process by identifying subgroups of patients. The results obtained can then be interactively modified by using an intuitive user interface. Researchers can also exchange the results from ICM with collaborators via a web link containing a Project ID number that will directly pull up the analysis results being shared. ICM also support incremental clustering that allows users to add new sample data into the data of a previous study to obtain a clustering result. Currently, the ICM web server is available with no login requirement and at no cost at http://biotech.bmi.ac.cn/icm/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Enhancing Privacy in Participatory Sensing Applications with Multidimensional Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Groat, Michael; Forrest, Stephanie; Horey, James L

2012-01-01

Participatory sensing applications rely on individuals to share local and personal data with others to produce aggregated models and knowledge. In this setting, privacy is an important consideration, and lack of privacy could discourage widespread adoption of many exciting applications. We present a privacy-preserving participatory sensing scheme for multidimensional data which uses negative surveys. Multidimensional data, such as vectors of attributes that include location and environment fields, pose a particular challenge for privacy protection and are common in participatory sensing applications. When reporting data in a negative survey, an individual participant randomly selects a value from the set complement ofmore » the sensed data value, once for each dimension, and returns the negative values to a central collection server. Using algorithms described in this paper, the server can reconstruct the probability density functions of the original distributions of sensed values, without knowing the participants actual data. As a consequence, complicated encryption and key management schemes are avoided, conserving energy. We study trade-offs between accuracy and privacy, and their relationships to the number of dimensions, categories, and participants. We introduce dimensional adjustment, a method that reduces the magnification of error associated with earlier work. Two simulation scenarios illustrate how the approach can protect the privacy of a participant's multidimensional data while allowing useful population information to be aggregated.« less

Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds.

PubMed

Uher, Vojtěch; Gajdoš, Petr; Radecký, Michal; Snášel, Václav

2016-01-01

The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price. It is popular for its simplicity and robustness. This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed. The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants. However, the DE has a great potential in the spatial data analysis and pattern recognition. This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions. It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs). The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs. The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population. A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced. The algorithm is tested on several spatial datasets and optimization problems. The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds.

Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds

PubMed Central

Radecký, Michal; Snášel, Václav

2016-01-01

The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price. It is popular for its simplicity and robustness. This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed. The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants. However, the DE has a great potential in the spatial data analysis and pattern recognition. This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions. It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs). The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs. The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population. A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced. The algorithm is tested on several spatial datasets and optimization problems. The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds. PMID:27974884

Accessing Multi-Dimensional Images and Data Cubes in the Virtual Observatory

NASA Astrophysics Data System (ADS)

Tody, Douglas; Plante, R. L.; Berriman, G. B.; Cresitello-Dittmar, M.; Good, J.; Graham, M.; Greene, G.; Hanisch, R. J.; Jenness, T.; Lazio, J.; Norris, P.; Pevunova, O.; Rots, A. H.

2014-01-01

Telescopes across the spectrum are routinely producing multi-dimensional images and datasets, such as Doppler velocity cubes, polarization datasets, and time-resolved “movies.” Examples of current telescopes producing such multi-dimensional images include the JVLA, ALMA, and the IFU instruments on large optical and near-infrared wavelength telescopes. In the near future, both the LSST and JWST will also produce such multi-dimensional images routinely. High-energy instruments such as Chandra produce event datasets that are also a form of multi-dimensional data, in effect being a very sparse multi-dimensional image. Ensuring that the data sets produced by these telescopes can be both discovered and accessed by the community is essential and is part of the mission of the Virtual Observatory (VO). The Virtual Astronomical Observatory (VAO, http://www.usvao.org/), in conjunction with its international partners in the International Virtual Observatory Alliance (IVOA), has developed a protocol and an initial demonstration service designed for the publication, discovery, and access of arbitrarily large multi-dimensional images. The protocol describing multi-dimensional images is the Simple Image Access Protocol, version 2, which provides the minimal set of metadata required to characterize a multi-dimensional image for its discovery and access. A companion Image Data Model formally defines the semantics and structure of multi-dimensional images independently of how they are serialized, while providing capabilities such as support for sparse data that are essential to deal effectively with large cubes. A prototype data access service has been deployed and tested, using a suite of multi-dimensional images from a variety of telescopes. The prototype has demonstrated the capability to discover and remotely access multi-dimensional data via standard VO protocols. The prototype informs the specification of a protocol that will be submitted to the IVOA for approval, with an operational data cube service to be delivered in mid-2014. An associated user-installable VO data service framework will provide the capabilities required to publish VO-compatible multi-dimensional images or data cubes.

Design of a compressed air modulator to be used in comprehensive multidimensional gas chromatography and its application in the determination of pesticide residues in grapes.

PubMed

Pizzutti, Ionara R; Vreuls, René J J; de Kok, André; Roehrs, Rafael; Martel, Samile; Friggi, Caroline A; Zanella, Renato

2009-04-10

In this study, a new modulator that is simple, robust and presents low operation costs, was developed. This modulator uses compressed air to cool two small portions in the first centimeters of the second chromatographic column of a comprehensive multidimensional gas chromatography (GCxGC) system. The results show a variation in the peak area less than 3 and 5% to alkanes and pesticides, respectively. The standard deviations for the retention times in the first and second dimension are around 0.05 min and 0.05s for all the compounds. The system was optimized with n-alkanes. The GCxGC system proposed was applied in the determination of pyrethroid pesticides (bifenthrin, cypermethrin, deltamethrin, fenvalerate, esfenvalerate, cis- and trans-permethrin) in grape samples. Samples were extracted by the mini-Luke modified method and pesticides were quantified by comprehensive multidimensional gas chromatography with micro electron-capture detection (microECD). The values of method limit of quantification (LOQ) were 0.01-0.02 mg kg(-1) for all studied pyrethroid and the values of recovery were between 94.3 and 115.2%, with good precision (RSD<18.4%), demonstrating that the performance of the total method consisting of a modified Luke extraction method and determination by GCxGC-microECD are satisfactory. This study also showed that the system using a modulator with a double jet of compressed air has the potential for application in the analysis of a wider range of pesticide residues in other commodities since it provides low values of LOQ with acceptable accuracy and precision.

Multidimensional Unfolding by Nonmetric Multidimensional Scaling of Spearman Distances in the Extended Permutation Polytope

ERIC Educational Resources Information Center

Van Deun, Katrijn; Heiser, Willem J.; Delbeke, Luc

2007-01-01

A multidimensional unfolding technique that is not prone to degenerate solutions and is based on multidimensional scaling of a complete data matrix is proposed: distance information about the unfolding data and about the distances both among judges and among objects is included in the complete matrix. The latter information is derived from the…

Redefining the utility of the three-isotope method

NASA Astrophysics Data System (ADS)

Cao, Xiaobin; Bao, Huiming

2017-09-01

The equilibrium isotope fractionation factor αeq is a fundamental parameter in the study of stable isotope effects. Experimentally, it has been difficult to establish that a system has attained equilibrium. The three-isotope method, using the initial trajectory of changing isotope ratios (e.g. 16O, 17O, and 18O) to deduce the final equilibrium point of isotope exchange, has long been hailed as the most rigorous experimental approach. However, over the years some researchers have cautioned on the limitations of this method, but the foundation of three-isotope method has not been properly examined and the method is still widely used in calibrating αeq for both traditional and increasingly non-traditional isotope systems today. Here, using water-water and dissolved CO2-water oxygen exchange as model systems, we conduct an isotopologues-specific kinetic analysis of the exchange processes and explore the underlying assumptions and validity of the three-isotope method. We demonstrate that without knowing the detailed exchange kinetics a priori the three-isotope method cannot lead to a reliable αeq. For a two-reservoir exchanging system, α determined by this method may be αeq, kinetic isotope effect, or apparent kinetic isotope effect, which can all bear different values. When multiple reservoirs exist during exchange, the evolving trajectory can be complex and hard to predict. Instead of being a tool for αeq determination, three-isotope method should be used as a tool for studying kinetic isotope effect, apparent kinetic isotope effect, and detailed exchange kinetics in diverse systems.

Prediction of free turbulent mixing using a turbulent kinetic energy method

NASA Technical Reports Server (NTRS)

Harsha, P. T.

1973-01-01

Free turbulent mixing of two-dimensional and axisymmetric one- and two-stream flows is analyzed by a relatively simple turbulent kinetic energy method. This method incorporates a linear relationship between the turbulent shear and the turbulent kinetic energy and an algebraic relationship for the length scale appearing in the turbulent kinetic energy equation. Good results are obtained for a wide variety of flows. The technique is shown to be especially applicable to flows with heat and mass transfer, for which nonunity Prandtl and Schmidt numbers may be assumed.

There's Method in Our Madness: Interpersonal Attraction as a Multidimensional Construct

ERIC Educational Resources Information Center

Latta, R. Michael

1976-01-01

Examines the similarity-attraction relationship using rating scale and bogus pipeline (a pseudophysiological monitoring device) techniques within the context of individual differences in social desirability biases and variations in experimental demands. (Author/RK)

Highly Transparent Water-Repelling Surfaces based on Biomimetic Hierarchical Structure

NASA Astrophysics Data System (ADS)

Wooh, Sanghyuk; Koh, Jai; Yoon, Hyunsik; Char, Kookheon

2013-03-01

Nature is a great source of inspiration for creating unique structures with special functions. The representative examples of water-repelling surfaces in nature, such as lotus leaves, rose petals, and insect wings, consist of an array of bumps (or long hairs) and nanoscale surface features with different dimension scales. Herein, we introduced a method of realizing multi-dimensional hierarchical structures and water-repellancy of the surfaces with different drop impact scenarios. The multi-dimensional hierarchical structures were fabricated by soft imprinting method with TiO2 nanoparticle pastes. In order to achieve the enhanced hydrophobicity, fluorinated moieties were attached to the etched surfaces to lower the surface energy. As a result, super-hydrophobic surfaces with high transparency were realized (over 176° water contact angle), and for further investigation, these hierarchical surfaces with different drop impact scenarios were characterized by varying the impact speed, drop size, and the geometry of the surfaces.

Systems and Methods for Data Visualization Using Three-Dimensional Displays

NASA Technical Reports Server (NTRS)

Davidoff, Scott (Inventor); Djorgovski, Stanislav G. (Inventor); Estrada, Vicente (Inventor); Donalek, Ciro (Inventor)

2017-01-01

Data visualization systems and methods for generating 3D visualizations of a multidimensional data space are described. In one embodiment a 3D data visualization application directs a processing system to: load a set of multidimensional data points into a visualization table; create representations of a set of 3D objects corresponding to the set of data points; receive mappings of data dimensions to visualization attributes; determine the visualization attributes of the set of 3D objects based upon the selected mappings of data dimensions to 3D object attributes; update a visibility dimension in the visualization table for each of the plurality of 3D object to reflect the visibility of each 3D object based upon the selected mappings of data dimensions to visualization attributes; and interactively render 3D data visualizations of the 3D objects within the virtual space from viewpoints determined based upon received user input.

New generic indexing technology

NASA Technical Reports Server (NTRS)

Freeston, Michael

1996-01-01

There has been no fundamental change in the dynamic indexing methods supporting database systems since the invention of the B-tree twenty-five years ago. And yet the whole classical approach to dynamic database indexing has long since become inappropriate and increasingly inadequate. We are moving rapidly from the conventional one-dimensional world of fixed-structure text and numbers to a multi-dimensional world of variable structures, objects and images, in space and time. But, even before leaving the confines of conventional database indexing, the situation is highly unsatisfactory. In fact, our research has led us to question the basic assumptions of conventional database indexing. We have spent the past ten years studying the properties of multi-dimensional indexing methods, and in this paper we draw the strands of a number of developments together - some quite old, some very new, to show how we now have the basis for a new generic indexing technology for the next generation of database systems.

Computer systems and methods for the query and visualization multidimensional databases

DOEpatents

Stolte, Chris; Tang, Diane L.; Hanrahan, Patrick

2017-04-25

A method of generating a data visualization is performed at a computer having a display, one or more processors, and memory. The memory stores one or more programs for execution by the one or more processors. The process receives user specification of a plurality of characteristics of a data visualization. The data visualization is based on data from a multidimensional database. The characteristics specify at least x-position and y-position of data marks corresponding to tuples of data retrieved from the database. The process generates a data visualization according to the specified plurality of characteristics. The data visualization has an x-axis defined based on data for one or more first fields from the database that specify x-position of the data marks and the data visualization has a y-axis defined based on data for one or more second fields from the database that specify y-position of the data marks.

Multidimensional heuristic process for high-yield production of astaxanthin and fragrance molecules in Escherichia coli.

PubMed

Zhang, Congqiang; Seow, Vui Yin; Chen, Xixian; Too, Heng-Phon

2018-05-11

Optimization of metabolic pathways consisting of large number of genes is challenging. Multivariate modular methods (MMMs) are currently available solutions, in which reduced regulatory complexities are achieved by grouping multiple genes into modules. However, these methods work well for balancing the inter-modules but not intra-modules. In addition, application of MMMs to the 15-step heterologous route of astaxanthin biosynthesis has met with limited success. Here, we expand the solution space of MMMs and develop a multidimensional heuristic process (MHP). MHP can simultaneously balance different modules by varying promoter strength and coordinating intra-module activities by using ribosome binding sites (RBSs) and enzyme variants. Consequently, MHP increases enantiopure 3S,3'S-astaxanthin production to 184 mg l -1 day -1 or 320 mg l -1 . Similarly, MHP improves the yields of nerolidol and linalool. MHP may be useful for optimizing other complex biochemical pathways.

Multidimensional Processing and Visual Rendering of Complex 3D Biomedical Images

NASA Technical Reports Server (NTRS)

Sams, Clarence F.

2016-01-01

The proposed technology uses advanced image analysis techniques to maximize the resolution and utility of medical imaging methods being used during spaceflight. We utilize COTS technology for medical imaging, but our applications require higher resolution assessment of the medical images than is routinely applied with nominal system software. By leveraging advanced data reduction and multidimensional imaging techniques utilized in analysis of Planetary Sciences and Cell Biology imaging, it is possible to significantly increase the information extracted from the onboard biomedical imaging systems. Year 1 focused on application of these techniques to the ocular images collected on ground test subjects and ISS crewmembers. Focus was on the choroidal vasculature and the structure of the optic disc. Methods allowed for increased resolution and quantitation of structural changes enabling detailed assessment of progression over time. These techniques enhance the monitoring and evaluation of crew vision issues during space flight.

Multi-attribute subjective evaluations of manual tracking tasks vs. objective performance of the human operator

NASA Technical Reports Server (NTRS)

Siapkaras, A.

1977-01-01

A computational method to deal with the multidimensional nature of tracking and/or monitoring tasks is developed. Operator centered variables, including the operator's perception of the task, are considered. Matrix ratings are defined based on multidimensional scaling techniques and multivariate analysis. The method consists of two distinct steps: (1) to determine the mathematical space of subjective judgements of a certain individual (or group of evaluators) for a given set of tasks and experimental conditionings; and (2) to relate this space with respect to both the task variables and the objective performance criteria used. Results for a variety of second-order trackings with smoothed noise-driven inputs indicate that: (1) many of the internally perceived task variables form a nonorthogonal set; and (2) the structure of the subjective space varies among groups of individuals according to the degree of familiarity they have with such tasks.

Iron oxide nanoparticle-based magnetic resonance method to monitor release kinetics from polymeric particles with high resolution.

PubMed

Chan, Minnie; Schopf, Eric; Sankaranarayanan, Jagadis; Almutairi, Adah

2012-09-18

A new method to precisely monitor rapid release kinetics from polymeric particles using super paramagnetic iron oxide nanoparticles, specifically by measuring spin-spin relaxation time (T(2)), is reported. Previously, we have published the formulation of logic gate particles from an acid-sensitive poly-β-aminoester ketal-2 polymer. Here, a series of poly-β-aminoester ketal-2 polymers with varying hydrophobicities were synthesized and used to formulate particles. We attempted to measure fluorescence of released Nile red to determine whether the structural adjustments could finely tune the release kinetics in the range of minutes to hours; however, this standard technique did not differentiate each release rate of our series. Thus, a new method based on encapsulation of iron oxide nanoparticles was developed, which enabled us to resolve the release kinetics of our particles. Moreover, the kinetics matched the relative hydrophobicity order determined by octanol-water partition coefficients. To the best of our knowledge, this method provides the highest resolution of release kinetics to date.

Hybrid finite element and Brownian dynamics method for diffusion-controlled reactions.

PubMed

Bauler, Patricia; Huber, Gary A; McCammon, J Andrew

2012-04-28

Diffusion is often the rate determining step in many biological processes. Currently, the two main computational methods for studying diffusion are stochastic methods, such as Brownian dynamics, and continuum methods, such as the finite element method. This paper proposes a new hybrid diffusion method that couples the strengths of each of these two methods. The method is derived for a general multidimensional system, and is presented using a basic test case for 1D linear and radially symmetric diffusion systems.

Kinetic analysis of overlapping multistep thermal decomposition comprising exothermic and endothermic processes: thermolysis of ammonium dinitramide.

PubMed

Muravyev, Nikita V; Koga, Nobuyoshi; Meerov, Dmitry B; Pivkina, Alla N

2017-01-25

This study focused on kinetic modeling of a specific type of multistep heterogeneous reaction comprising exothermic and endothermic reaction steps, as exemplified by the practical kinetic analysis of the experimental kinetic curves for the thermal decomposition of molten ammonium dinitramide (ADN). It is known that the thermal decomposition of ADN occurs as a consecutive two step mass-loss process comprising the decomposition of ADN and subsequent evaporation/decomposition of in situ generated ammonium nitrate. These reaction steps provide exothermic and endothermic contributions, respectively, to the overall thermal effect. The overall reaction process was deconvoluted into two reaction steps using simultaneously recorded thermogravimetry and differential scanning calorimetry (TG-DSC) curves by considering the different physical meanings of the kinetic data derived from TG and DSC by P value analysis. The kinetic data thus separated into exothermic and endothermic reaction steps were kinetically characterized using kinetic computation methods including isoconversional method, combined kinetic analysis, and master plot method. The overall kinetic behavior was reproduced as the sum of the kinetic equations for each reaction step considering the contributions to the rate data derived from TG and DSC. During reproduction of the kinetic behavior, the kinetic parameters and contributions of each reaction step were optimized using kinetic deconvolution analysis. As a result, the thermal decomposition of ADN was successfully modeled as partially overlapping exothermic and endothermic reaction steps. The logic of the kinetic modeling was critically examined, and the practical usefulness of phenomenological modeling for the thermal decomposition of ADN was illustrated to demonstrate the validity of the methodology and its applicability to similar complex reaction processes.

Quantification of metabotropic glutamate subtype 5 receptors in the brain by an equilibrium method using 18F-SP203.

PubMed

Kimura, Yasuyuki; Siméon, Fabrice G; Zoghbi, Sami S; Zhang, Yi; Hatazawa, Jun; Pike, Victor W; Innis, Robert B; Fujita, Masahiro

2012-02-01

A new PET ligand, 3-fluoro-5-(2-(2-(18)F-(fluoromethyl)-thiazol-4-yl)ethynyl)benzonitrile (18F-SP203) can quantify metabotropic glutamate subtype 5 receptors (mGluR5) in human brain by a bolus injection and kinetic modeling. As an alternative approach to a bolus injection, binding can simply be measured as a ratio of tissue to metabolite-corrected plasma at a single time point under equilibrium conditions achieved by administering the radioligand with a bolus injection followed by a constant infusion. The purpose of this study was to validate the equilibrium method as an alternative to the standard kinetic method for measuring 18F-SP203 binding in the brain. Nine healthy subjects were injected with 18F-SP203 using a bolus plus constant infusion for 300 min. A single ratio of bolus-to-constant infusion (the activity of bolus equaled to that of infusion over 219 min) was applied to all subjects to achieve equilibrium in approximately 120 min. As a measure of ligand binding, we compared total distribution volume (VT) calculated by the equilibrium and kinetic methods in each scan. The equilibrium method calculated VT by the ratio of radioactivity in the brain to the concentration of 18F-SP203 in arterial plasma at 120 min, and the kinetic method calculated VT by a two-tissue compartment model using brain and plasma dynamic data from 0 to 120 min. VT obtained via the equilibrium method was highly correlated with VT obtained via kinetic modeling. Inter-subject variability of VT obtained via the equilibrium method was slightly smaller than VT obtained via the kinetic method. VT obtained via the equilibrium method was ~10% higher than VT obtained via the kinetic method, indicating a small difference between the measurements. Taken together, the results of this study show that using the equilibrium method is an acceptable alternative to the standard kinetic method when using 18F-SP203 to measure mGluR5. Although small differences in the measurements obtained via the equilibrium and kinetic methods exist, both methods consistently measured mGluR5 as indicated by the highly correlated VT values; the equilibrium method was slightly more precise, as indirectly measured by the smaller coefficient of variability across subjects. In addition, when using 18F-SP203, the equilibrium method is more efficient because it requires much less data. Copyright © 2011. Published by Elsevier Inc.

Multidimensional k-nearest neighbor model based on EEMD for financial time series forecasting

NASA Astrophysics Data System (ADS)

Zhang, Ningning; Lin, Aijing; Shang, Pengjian

2017-07-01

In this paper, we propose a new two-stage methodology that combines the ensemble empirical mode decomposition (EEMD) with multidimensional k-nearest neighbor model (MKNN) in order to forecast the closing price and high price of the stocks simultaneously. The modified algorithm of k-nearest neighbors (KNN) has an increasingly wide application in the prediction of all fields. Empirical mode decomposition (EMD) decomposes a nonlinear and non-stationary signal into a series of intrinsic mode functions (IMFs), however, it cannot reveal characteristic information of the signal with much accuracy as a result of mode mixing. So ensemble empirical mode decomposition (EEMD), an improved method of EMD, is presented to resolve the weaknesses of EMD by adding white noise to the original data. With EEMD, the components with true physical meaning can be extracted from the time series. Utilizing the advantage of EEMD and MKNN, the new proposed ensemble empirical mode decomposition combined with multidimensional k-nearest neighbor model (EEMD-MKNN) has high predictive precision for short-term forecasting. Moreover, we extend this methodology to the case of two-dimensions to forecast the closing price and high price of the four stocks (NAS, S&P500, DJI and STI stock indices) at the same time. The results indicate that the proposed EEMD-MKNN model has a higher forecast precision than EMD-KNN, KNN method and ARIMA.

Application of information-retrieval methods to the classification of physical data

NASA Technical Reports Server (NTRS)

Mamotko, Z. N.; Khorolskaya, S. K.; Shatrovskiy, L. I.

1975-01-01

Scientific data received from satellites are characterized as a multi-dimensional time series, whose terms are vector functions of a vector of measurement conditions. Information retrieval methods are used to construct lower dimensional samples on the basis of the condition vector, in order to obtain these data and to construct partial relations. The methods are applied to the joint Soviet-French Arkad project.

Computer object segmentation by nonlinear image enhancement, multidimensional clustering, and geometrically constrained contour optimization

NASA Astrophysics Data System (ADS)

Bruynooghe, Michel M.

1998-04-01

In this paper, we present a robust method for automatic object detection and delineation in noisy complex images. The proposed procedure is a three stage process that integrates image segmentation by multidimensional pixel clustering and geometrically constrained optimization of deformable contours. The first step is to enhance the original image by nonlinear unsharp masking. The second step is to segment the enhanced image by multidimensional pixel clustering, using our reducible neighborhoods clustering algorithm that has a very interesting theoretical maximal complexity. Then, candidate objects are extracted and initially delineated by an optimized region merging algorithm, that is based on ascendant hierarchical clustering with contiguity constraints and on the maximization of average contour gradients. The third step is to optimize the delineation of previously extracted and initially delineated objects. Deformable object contours have been modeled by cubic splines. An affine invariant has been used to control the undesired formation of cusps and loops. Non linear constrained optimization has been used to maximize the external energy. This avoids the difficult and non reproducible choice of regularization parameters, that are required by classical snake models. The proposed method has been applied successfully to the detection of fine and subtle microcalcifications in X-ray mammographic images, to defect detection by moire image analysis, and to the analysis of microrugosities of thin metallic films. The later implementation of the proposed method on a digital signal processor associated to a vector coprocessor would allow the design of a real-time object detection and delineation system for applications in medical imaging and in industrial computer vision.

Radiative interactions in multi-dimensional chemically reacting flows using Monte Carlo simulations

NASA Technical Reports Server (NTRS)

Liu, Jiwen; Tiwari, Surendra N.

1994-01-01

The Monte Carlo method (MCM) is applied to analyze radiative heat transfer in nongray gases. The nongray model employed is based on the statistical narrow band model with an exponential-tailed inverse intensity distribution. The amount and transfer of the emitted radiative energy in a finite volume element within a medium are considered in an exact manner. The spectral correlation between transmittances of two different segments of the same path in a medium makes the statistical relationship different from the conventional relationship, which only provides the non-correlated results for nongray methods is discussed. Validation of the Monte Carlo formulations is conducted by comparing results of this method of other solutions. In order to further establish the validity of the MCM, a relatively simple problem of radiative interactions in laminar parallel plate flows is considered. One-dimensional correlated Monte Carlo formulations are applied to investigate radiative heat transfer. The nongray Monte Carlo solutions are also obtained for the same problem and they also essentially match the available analytical solutions. the exact correlated and non-correlated Monte Carlo formulations are very complicated for multi-dimensional systems. However, by introducing the assumption of an infinitesimal volume element, the approximate correlated and non-correlated formulations are obtained which are much simpler than the exact formulations. Consideration of different problems and comparison of different solutions reveal that the approximate and exact correlated solutions agree very well, and so do the approximate and exact non-correlated solutions. However, the two non-correlated solutions have no physical meaning because they significantly differ from the correlated solutions. An accurate prediction of radiative heat transfer in any nongray and multi-dimensional system is possible by using the approximate correlated formulations. Radiative interactions are investigated in chemically reacting compressible flows of premixed hydrogen and air in an expanding nozzle. The governing equations are based on the fully elliptic Navier-Stokes equations. Chemical reaction mechanisms were described by a finite rate chemistry model. The correlated Monte Carlo method developed earlier was employed to simulate multi-dimensional radiative heat transfer. Results obtained demonstrate that radiative effects on the flowfield are minimal but radiative effects on the wall heat transfer are significant. Extensive parametric studies are conducted to investigate the effects of equivalence ratio, wall temperature, inlet flow temperature, and nozzle size on the radiative and conductive wall fluxes.

Nmrglue: an open source Python package for the analysis of multidimensional NMR data.

PubMed

Helmus, Jonathan J; Jaroniec, Christopher P

2013-04-01

Nmrglue, an open source Python package for working with multidimensional NMR data, is described. When used in combination with other Python scientific libraries, nmrglue provides a highly flexible and robust environment for spectral processing, analysis and visualization and includes a number of common utilities such as linear prediction, peak picking and lineshape fitting. The package also enables existing NMR software programs to be readily tied together, currently facilitating the reading, writing and conversion of data stored in Bruker, Agilent/Varian, NMRPipe, Sparky, SIMPSON, and Rowland NMR Toolkit file formats. In addition to standard applications, the versatility offered by nmrglue makes the package particularly suitable for tasks that include manipulating raw spectrometer data files, automated quantitative analysis of multidimensional NMR spectra with irregular lineshapes such as those frequently encountered in the context of biomacromolecular solid-state NMR, and rapid implementation and development of unconventional data processing methods such as covariance NMR and other non-Fourier approaches. Detailed documentation, install files and source code for nmrglue are freely available at http://nmrglue.com. The source code can be redistributed and modified under the New BSD license.

Nmrglue: An Open Source Python Package for the Analysis of Multidimensional NMR Data

PubMed Central

Helmus, Jonathan J.; Jaroniec, Christopher P.

2013-01-01

Nmrglue, an open source Python package for working with multidimensional NMR data, is described. When used in combination with other Python scientific libraries, nmrglue provides a highly flexible and robust environment for spectral processing, analysis and visualization and includes a number of common utilities such as linear prediction, peak picking and lineshape fitting. The package also enables existing NMR software programs to be readily tied together, currently facilitating the reading, writing and conversion of data stored in Bruker, Agilent/Varian, NMRPipe, Sparky, SIMPSON, and Rowland NMR Toolkit file formats. In addition to standard applications, the versatility offered by nmrglue makes the package particularly suitable for tasks that include manipulating raw spectrometer data files, automated quantitative analysis of multidimensional NMR spectra with irregular lineshapes such as those frequently encountered in the context of biomacromolecular solid-state NMR, and rapid implementation and development of unconventional data processing methods such as covariance NMR and other non-Fourier approaches. Detailed documentation, install files and source code for nmrglue are freely available at http://nmrglue.com. The source code can be redistributed and modified under the New BSD license. PMID:23456039

Testlet-Based Multidimensional Adaptive Testing.

PubMed

Frey, Andreas; Seitz, Nicki-Nils; Brandt, Steffen

2016-01-01

Multidimensional adaptive testing (MAT) is a highly efficient method for the simultaneous measurement of several latent traits. Currently, no psychometrically sound approach is available for the use of MAT in testlet-based tests. Testlets are sets of items sharing a common stimulus such as a graph or a text. They are frequently used in large operational testing programs like TOEFL, PISA, PIRLS, or NAEP. To make MAT accessible for such testing programs, we present a novel combination of MAT with a multidimensional generalization of the random effects testlet model (MAT-MTIRT). MAT-MTIRT compared to non-adaptive testing is examined for several combinations of testlet effect variances (0.0, 0.5, 1.0, and 1.5) and testlet sizes (3, 6, and 9 items) with a simulation study considering three ability dimensions with simple loading structure. MAT-MTIRT outperformed non-adaptive testing regarding the measurement precision of the ability estimates. Further, the measurement precision decreased when testlet effect variances and testlet sizes increased. The suggested combination of the MTIRT model therefore provides a solution to the substantial problems of testlet-based tests while keeping the length of the test within an acceptable range.

The Pursuit of Happiness Measurement: A Psychometric Model Based on Psychophysiological Correlates

PubMed Central

Pietro, Cipresso; Silvia, Serino; Giuseppe, Riva

2014-01-01

Everyone is interested in the pursuit of happiness, but the real problem for the researchers is how to measure it. Our aim was to deeply investigate happiness measurement through biomedical signals, using psychophysiological methods to objectify the happiness experiences measurements. The classic valence-arousal model of affective states to study happiness has been extensively used in psychophysiology. However, really few studies considered a real combination of these two dimensions and no study further investigated multidimensional models. More, most studies focused mainly on self-report to measure happiness and a deeper psychophysiological investigation on the dimensions of such an experience is still missing. A multidimensional model of happiness is presented and both the dimensions and the measures extracted within each dimension are comprehensively explained. This multidimensional model aims at being a milestone for future systematic study on psychophysiology of happiness and affective states. It seems everyone has a view on happiness. Joan Collins, theDalai Lama and over 100 others have released new titles on the subject since the beginning of 2001 Richard Tooth “The Psychology of Happiness (2nd Edition)”Michael Argyle, Routledge PMID:24955383

The Four Faces of Competition: The Development of the Multidimensional Competitive Orientation Inventory

PubMed Central

Orosz, Gábor; Tóth-Király, István; Büki, Noémi; Ivaskevics, Krisztián; Bőthe, Beáta; Fülöp, Márta

2018-01-01

To date, no short scale exists with established factor structure that can assess individual differences in competition. The aim of the present study was to uncover and operationalize the facets of competitive orientations with theoretical underpinning and strong psychometric properties. A total of 2676 respondents were recruited for four studies. The items were constructed based on qualitative research in different cultural contexts. A combined method of exploratory structural equation modeling (ESEM) and confirmatory factor analysis (CFA) was employed. ESEM resulted in a four-factor structure of the competitive orientations and this structure was supported by a series of CFAs on different comprehensive samples. The Multidimensional Competitive Orientation Inventory (MCOI) included 12 items and four factors: hypercompetitive orientation, self-developmental competitive orientation, anxiety-driven competition avoidance, and lack of interest toward competition. Strong gender invariance was established. The four facets of competition have differentiated relationship patterns with adaptive and maladaptive personality and motivational constructs. The MCOI can assess the adaptive and maladaptive facets of competitive orientations with a short, reliable, valid and theoretically underlined multidimensional measure. PMID:29872415

The Impact of Kt/V Urea-Based Dialysis Adequacy on Quality of Life and Adherence in Haemodialysis Patients: A Cross-Sectional Study in Greece.

PubMed

Theofilou, Paraskevi; Togas, Constantinos; Vasilopoulou, Chrysoula; Minos, Christos; Zyga, Sofia; Tzitzikos, Giorgos

2015-04-13

There is clear evidence of a link between dialysis adequacy (as measured by urea kinetic modeling or urea reduction ratio) and such important clinical outcomes as morbidity and mortality. Evidence regarding the relationship between dialysis adequacy and quality of life (QOL) outcomes as well as adherence is less clear. The present paper is a study protocol which is planning to answer the following research question: what is the impact of dialysis adequacy on QOL and adherence in a sample of hemodialysis patients? The final sample size will be around 100 patients undergoing hemodialysis. Each subject's QOL and adherence will be measured using the following instruments: i) the Missoula-VITAS quality of life index 25; ii) the multidimensional scale of perceived social support and iii) the simplified medication adherence questionnaire. Dialysis adequacy is expected to be related to QOL and adherence scores.

Early Amyloidogenic Oligomerization Studied through Fluorescence Lifetime Correlation Spectroscopy

PubMed Central

Paredes, Jose M.; Casares, Salvador; Ruedas-Rama, Maria J.; Fernandez, Elena; Castello, Fabio; Varela, Lorena; Orte, Angel

2012-01-01

Amyloidogenic protein aggregation is a persistent biomedical problem. Despite active research in disease-related aggregation, the need for multidisciplinary approaches to the problem is evident. Recent advances in single-molecule fluorescence spectroscopy are valuable for examining heterogenic biomolecular systems. In this work, we have explored the initial stages of amyloidogenic aggregation by employing fluorescence lifetime correlation spectroscopy (FLCS), an advanced modification of conventional fluorescence correlation spectroscopy (FCS) that utilizes time-resolved information. FLCS provides size distributions and kinetics for the oligomer growth of the SH3 domain of α-spectrin, whose N47A mutant forms amyloid fibrils at pH 3.2 and 37 °C in the presence of salt. The combination of FCS with additional fluorescence lifetime information provides an exciting approach to focus on the initial aggregation stages, allowing a better understanding of the fibrillization process, by providing multidimensional information, valuable in combination with other conventional methodologies. PMID:22949804

Combined effects of trapped energetic ions and resistive layer damping on the stability of the resistive wall mode

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Yuling; Liu, Yue, E-mail: Yueqiang.Liu@ccfe.ac.uk, E-mail: liuyue@dlut.edu.cn; Liu, Chao

2016-01-15

A dispersion relation is derived for the stability of the resistive wall mode (RWM), which includes both the resistive layer damping physics and the toroidal precession drift resonance damping from energetic ions in tokamak plasmas. The dispersion relation is numerically solved for a model plasma, for the purpose of systematic investigation of the RWM stability in multi-dimensional plasma parameter space including the plasma resistivity, the radial location of the resistive wall, as well as the toroidal flow velocity. It is found that the toroidal favorable average curvature in the resistive layer contributes a significant stabilization of the RWM. This stabilizationmore » is further enhanced by adding the drift kinetic contribution from energetic ions. Furthermore, two traditionally assumed inner layer models are considered and compared in the dispersion relation, resulting in different predictions for the stability of the RWM.« less

Analysis of Material Sample Heated by Impinging Hot Hydrogen Jet in a Non-Nuclear Tester

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Foote, John; Litchford, Ron

2006-01-01

A computational conjugate heat transfer methodology was developed and anchored with data obtained from a hot-hydrogen jet heated, non-nuclear materials tester, as a first step towards developing an efficient and accurate multiphysics, thermo-fluid computational methodology to predict environments for hypothetical solid-core, nuclear thermal engine thrust chamber. The computational methodology is based on a multidimensional, finite-volume, turbulent, chemically reacting, thermally radiating, unstructured-grid, and pressure-based formulation. The multiphysics invoked in this study include hydrogen dissociation kinetics and thermodynamics, turbulent flow, convective and thermal radiative, and conjugate heat transfers. Predicted hot hydrogen jet and material surface temperatures were compared with those of measurement. Predicted solid temperatures were compared with those obtained with a standard heat transfer code. The interrogation of physics revealed that reactions of hydrogen dissociation and recombination are highly correlated with local temperature and are necessary for accurate prediction of the hot-hydrogen jet temperature.

Spray and High-Pressure Flow Computations in the National Combustion Code (NCC) Improved

NASA Technical Reports Server (NTRS)

Raju, Manthena S.

2002-01-01

Sprays occur in a wide variety of industrial and power applications and in materials processing. A liquid spray is a two-phase flow with a gas as the continuous phase and a liquid as the dispersed phase in the form of droplets or ligaments. The interactions between the two phases--which are coupled through exchanges of mass, momentum, and energy--can occur in different ways at disparate time and length scales involving various thermal, mass, and fluid dynamic factors. An understanding of the flow, combustion, and thermal properties of a rapidly vaporizing spray requires careful modeling of the ratecontrolling processes associated with turbulent transport, mixing, chemical kinetics, evaporation, and spreading rates of the spray, among many other factors. With the aim of developing an efficient solution procedure for use in multidimensional combustor modeling, researchers at the NASA Glenn Research Center have advanced the state-of-the-art in spray computations in several important ways.

Embedding of multidimensional time-dependent observations.

PubMed

Barnard, J P; Aldrich, C; Gerber, M

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

Embedding of multidimensional time-dependent observations

NASA Astrophysics Data System (ADS)

Barnard, Jakobus P.; Aldrich, Chris; Gerber, Marius

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

Using Multidimensional Methods to Understand the Development, Interpretation and Enactment of Quality Assurance Policy within the Educational Development Community

ERIC Educational Resources Information Center

Smith, Karen

2018-01-01

Policy texts are representations of practice that both reflect and shape the world around them. There is, however, little higher education research that critically analyses the impact of higher education policy on educational developers and educational development practice. Extending methods from critical discourse analysis by combining textual…

Impact of Violation of the Missing-at-Random Assumption on Full-Information Maximum Likelihood Method in Multidimensional Adaptive Testing

ERIC Educational Resources Information Center

Han, Kyung T.; Guo, Fanmin

2014-01-01

The full-information maximum likelihood (FIML) method makes it possible to estimate and analyze structural equation models (SEM) even when data are partially missing, enabling incomplete data to contribute to model estimation. The cornerstone of FIML is the missing-at-random (MAR) assumption. In (unidimensional) computerized adaptive testing…

Approaching Multidimensional Forms of Knowledge through Personal Meaning Mapping in Science Integrating Teaching outside the Classroom

ERIC Educational Resources Information Center

Hartmeyer, Rikke; Bølling, Mads; Bentsen, Peter

2017-01-01

Current research points to Personal Meaning Mapping (PMM) as a method useful in investigating students' prior and current science knowledge. However, studies investigating PMM as a method for exploring specific knowledge dimensions are lacking. Ensuring that students are able to access specific knowledge dimensions is important, especially in…

A Conditional Exposure Control Method for Multidimensional Adaptive Testing

ERIC Educational Resources Information Center

Finkelman, Matthew; Nering, Michael L.; Roussos, Louis A.

2009-01-01

In computerized adaptive testing (CAT), ensuring the security of test items is a crucial practical consideration. A common approach to reducing item theft is to define maximum item exposure rates, i.e., to limit the proportion of examinees to whom a given item can be administered. Numerous methods for controlling exposure rates have been proposed…

Transcending the Quantitative-Qualitative Divide with Mixed Methods Research: A Multidimensional Framework for Understanding Congruence and Completeness in the Study of Values

ERIC Educational Resources Information Center

McLafferty, Charles L., Jr.; Slate, John R.; Onwuegbuzie, Anthony J.

2010-01-01

Quantitative research dominates published literature in the helping professions. Mixed methods research, which integrates quantitative and qualitative methodologies, has received a lukewarm reception. The authors address the iterative separation that infuses theory, praxis, philosophy, methodology, training, and public perception and propose a…

Estimation of Free Radical Ionization Energies by the Kinetic Method and the Relationship between the Kinetic Method and the Hammett Equation.

PubMed

Chen, G; Wong, P; Cooks, R G

1997-09-01

Substituted 1,2-diphenylethanes undergo competitive dissociations upon electron ionization (EI) to generate substituted benzyl cation and benzyl radical pairs. Application of the kinetic method to the previous reported EI mass spectra of these covalently bound precursor ions (data are taken from McLafferty et al. J. Am. Chem. Soc. 1970, 92, 6867)) is used to estimate the ionization energies of substituted benzyl free radicals. A correlation is observed between the Hammett σ constant of the substituents and the kinetic method parameter, ln(k(x)/k(H)), where k(x) is the rate of fragmentation to give the substituted product ion and k(H) is the rate to give the benzyl ion itself. Systems involving weakly bound cluster ions, including proton-bound dimers of meta- and para-substituted pyridines and meta- and para-substituted anilines, and electron-bound dimers of meta- and para-substituted nitrobenzenes, also show good correlations between the kinetic method parameter and the Hammett σ constant.

Multidimensional structured data visualization method and apparatus, text visualization method and apparatus, method and apparatus for visualizing and graphically navigating the world wide web, method and apparatus for visualizing hierarchies

DOEpatents

Risch, John S [Kennewick, WA; Dowson, Scott T [West Richland, WA; Hart, Michelle L [Richland, WA; Hatley, Wes L [Kennewick, WA

2008-05-13

A method of displaying correlations among information objects comprises receiving a query against a database; obtaining a query result set; and generating a visualization representing the components of the result set, the visualization including one of a plane and line to represent a data field, nodes representing data values, and links showing correlations among fields and values. Other visualization methods and apparatus are disclosed.

Multidimensional structured data visualization method and apparatus, text visualization method and apparatus, method and apparatus for visualizing and graphically navigating the world wide web, method and apparatus for visualizing hierarchies

DOEpatents

Risch, John S [Kennewick, WA; Dowson, Scott T [West Richland, WA

2012-03-06

A method of displaying correlations among information objects includes receiving a query against a database; obtaining a query result set; and generating a visualization representing the components of the result set, the visualization including one of a plane and line to represent a data field, nodes representing data values, and links showing correlations among fields and values. Other visualization methods and apparatus are disclosed.

On the Need for Multidimensional Stirling Simulations

NASA Technical Reports Server (NTRS)

Dyson, Rodger W.; Wilson, Scott D.; Tew, Roy C.; Demko, Rikako

2005-01-01

Given the cost and complication of simulating Stirling convertors, do we really need multidimensional modeling when one-dimensional capabilities exist? This paper provides a comprehensive description of when and why multidimensional simulation is needed.

Spectral method for a kinetic swarming model

DOE PAGES

Gamba, Irene M.; Haack, Jeffrey R.; Motsch, Sebastien

2015-04-28

Here we present the first numerical method for a kinetic description of the Vicsek swarming model. The kinetic model poses a unique challenge, as there is a distribution dependent collision invariant to satisfy when computing the interaction term. We use a spectral representation linked with a discrete constrained optimization to compute these interactions. To test the numerical scheme we investigate the kinetic model at different scales and compare the solution with the microscopic and macroscopic descriptions of the Vicsek model. Lastly, we observe that the kinetic model captures key features such as vortex formation and traveling waves.

Cathepsin D immobilized capillary reactors for on-flow screening assays.

PubMed

Cornelio, Vivian Estevam; de Moraes, Marcela Cristina; Domingues, Vanessa de Cassia; Fernandes, João Batista; da Silva, Maria Fátima das Gracas Fernandes; Cass, Quezia Bezerra; Vieira, Paulo Cezar

2018-03-20

The treatment of diseases using enzymes as targets has called for the development of new and reliable methods for screening. The protease cathepsin D is one such target involved in several diseases such as tumors, degenerative processes, and vital processes of parasites causing schistosomiasis. Herein, we describe the preparation of a fused silica capillary, cathepsin D (CatD)-immobilized enzyme reactor (IMER) using in a multidimensional High Performance Liquid Chromatography-based method (2D-HPLC) and zonal affinity chromatography as an alternative in the search for new ligands. The activity and kinetic parameters of CatD-IMER were evaluated by monitoring the product MOCAc-Gly-Lys-Pro-Ile-Leu-Phe (P-MOCAc) (K M  = 81.9 ± 7.49 μmol/L) generated by cleavage of the fluorogenic substrate MOCAc-Gly-Lys-Pro-Ile-Leu-Phe-Phe-Arg-Leu-Lys(DNP)-d-Arg-NH2 (S-MOCAc). Stability studies have indicated that CatD-IMER retained 20% of activity after 5 months, a relevant result, because proteases are susceptible to autoproteolysis in solution assays with free enzyme. In the search for inhibitors, 12 crude natural product extracts were analyzed using CatD-IMER as the target, resulting in the isolation of different classes of natural products. In addition, 26 compounds obtained from different species of plants were also screened, demonstrating the efficiency and reproducibility of the herein reported assay even in the case of complex matrices such as plant crude extracts. Copyright © 2018 Elsevier B.V. All rights reserved.

A ring polymer molecular dynamics study of the isotopologues of the H + H2 reaction.

PubMed

Suleimanov, Yury V; de Tudela, Ricardo Pérez; Jambrina, Pablo G; Castillo, Jesús F; Sáez-Rábanos, Vicente; Manolopoulos, David E; Aoiz, F Javier

2013-03-14

The inclusion of Quantum Mechanical (QM) effects such as zero point energy (ZPE) and tunneling in simulations of chemical reactions, especially in the case of light atom transfer, is an important problem in computational chemistry. In this respect, the hydrogen exchange reaction and its isotopic variants constitute an excellent benchmark for the assessment of approximate QM methods. In particular, the recently developed ring polymer molecular dynamics (RPMD) technique has been demonstrated to give very good results for bimolecular chemical reactions in the gas phase. In this work, we have performed a detailed RPMD study of the H + H(2) reaction and its isotopologues Mu + H(2), D + H(2) and Heμ + H(2), at temperatures ranging from 200 to 1000 K. Thermal rate coefficients and kinetic isotope effects have been computed and compared with exact QM calculations as well as with quasiclassical trajectories and experiment. The agreement with the QM results is good for the heaviest isotopologues, with errors ranging from 15% to 45%, and excellent for Mu + H(2), with errors below 15%. We have seen that RPMD is able to capture the ZPE effect very accurately, a desirable feature of any method based on molecular dynamics. We have also verified Richardson and Althorpe's prediction [J. O. Richardson and S. C. Althorpe, J. Chem. Phys., 2009, 131, 214106] that RPMD will overestimate thermal rates for asymmetric reactions and underestimate them for symmetric reactions in the deep tunneling regime. The ZPE effect along the reaction coordinate must be taken into account when assigning the reaction symmetry in the multidimensional case.

Multidimensional Scaling in the Poincare Disk

DTIC Science & Technology

2011-05-01

REPORT Multidimensional Scaling in the Poincare Dis 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: Multidimensional scaling (MDS) is a class of projective...DATES COVERED (From - To) Standard Form 298 (Rev 8/98) Prescribed by ANSI Std. Z39.18 - Multidimensional Scaling in the Poincare Dis Report Title... plane . Our construction is based on an approximate hyperbolic line search and exempli?es some of the particulars that need to be addressed when

Methods for Kinetic and Thermodynamic Analysis of Aminoacyl-tRNA Synthetases

PubMed Central

Francklyn, Christopher S.; First, Eric A.; Perona, John J.; Hou, Ya-Ming

2008-01-01

The accuracy of protein synthesis relies on the ability of aminoacyl-tRNA synthetases (aaRSs) to discriminate among true and near cognate substrates. To date, analysis of aaRSs function, including identification of residues of aaRS participating in amino acid and tRNA discrimination, has largely relied on the steady state kinetic pyrophosphate exchange and aminoacylation assays. Pre-steady state kinetic studies investigating a more limited set of aaRS systems have also been undertaken to assess the energetic contributions of individual enzyme-substrate interactions, particularly in the adenylation half reaction. More recently, a renewed interest in the use of rapid kinetics approaches for aaRSs has led to their application to several new aaRS systems, resulting in the identification of mechanistic differences that distinguish the two structurally distinct aaRS classes. Here, we review the techniques for thermodynamic and kinetic analysis of aaRS function. Following a brief survey of methods for the preparation of materials and for steady state kinetic analysis, this review will describe pre-steady state kinetic methods employing rapid quench and stopped-flow fluorescence for analysis of the activation and aminoacyl transfer reactions. Application of these methods to any aaRS system allows the investigator to derive detailed kinetic mechanisms for the activation and aminoacyl transfer reactions, permitting issues of substrate specificity, stereochemical mechanism, and inhibitor interaction to be addressed in a rigorous and quantitative fashion. PMID:18241792

The SIETTE Automatic Assessment Environment

ERIC Educational Resources Information Center

Conejo, Ricardo; Guzmán, Eduardo; Trella, Monica

2016-01-01

This article describes the evolution and current state of the domain-independent Siette assessment environment. Siette supports different assessment methods--including classical test theory, item response theory, and computer adaptive testing--and integrates them with multidimensional student models used by intelligent educational systems.…

Rapid acquisition of data dense solid-state CPMG NMR spectral sets using multi-dimensional statistical analysis

DOE PAGES

Mason, H. E.; Uribe, E. C.; Shusterman, J. A.

2018-01-01

Tensor-rank decomposition methods have been applied to variable contact time 29 Si{ 1 H} CP/CPMG NMR data sets to extract NMR dynamics information and dramatically decrease conventional NMR acquisition times.

Empirical Identification of Hierarchies.

ERIC Educational Resources Information Center

McCormick, Douglas; And Others

Outlining a cluster procedure which maximizes specific criteria while building scales from binary measures using a sequential, agglomerative, overlapping, non-hierarchic method results in indices giving truer results than exploratory facotr analyses or multidimensional scaling. In a series of eleven figures, patterns within cluster histories…

Rapid acquisition of data dense solid-state CPMG NMR spectral sets using multi-dimensional statistical analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mason, H. E.; Uribe, E. C.; Shusterman, J. A.

Tensor-rank decomposition methods have been applied to variable contact time 29 Si{ 1 H} CP/CPMG NMR data sets to extract NMR dynamics information and dramatically decrease conventional NMR acquisition times.

Scaling Laws for the Multidimensional Burgers Equation with Quadratic External Potential

NASA Astrophysics Data System (ADS)

Leonenko, N. N.; Ruiz-Medina, M. D.

2006-07-01

The reordering of the multidimensional exponential quadratic operator in coordinate-momentum space (see X. Wang, C.H. Oh and L.C. Kwek (1998). J. Phys. A.: Math. Gen. 31:4329-4336) is applied to derive an explicit formulation of the solution to the multidimensional heat equation with quadratic external potential and random initial conditions. The solution to the multidimensional Burgers equation with quadratic external potential under Gaussian strongly dependent scenarios is also obtained via the Hopf-Cole transformation. The limiting distributions of scaling solutions to the multidimensional heat and Burgers equations with quadratic external potential are then obtained under such scenarios.

A Novel Multi-Scale Domain Overlapping CFD/STH Coupling Methodology for Multi-Dimensional Flows Relevant to Nuclear Applications

NASA Astrophysics Data System (ADS)

Grunloh, Timothy P.

The objective of this dissertation is to develop a 3-D domain-overlapping coupling method that leverages the superior flow field resolution of the Computational Fluid Dynamics (CFD) code STAR-CCM+ and the fast execution of the System Thermal Hydraulic (STH) code TRACE to efficiently and accurately model thermal hydraulic transport properties in nuclear power plants under complex conditions of regulatory and economic importance. The primary contribution is the novel Stabilized Inertial Domain Overlapping (SIDO) coupling method, which allows for on-the-fly correction of TRACE solutions for local pressures and velocity profiles inside multi-dimensional regions based on the results of the CFD simulation. The method is found to outperform the more frequently-used domain decomposition coupling methods. An STH code such as TRACE is designed to simulate large, diverse component networks, requiring simplifications to the fluid flow equations for reasonable execution times. Empirical correlations are therefore required for many sub-grid processes. The coarse grids used by TRACE diminish sensitivity to small scale geometric details such as Reactor Pressure Vessel (RPV) internals. A CFD code such as STAR-CCM+ uses much finer computational meshes that are sensitive to the geometric details of reactor internals. In turbulent flows, it is infeasible to fully resolve the flow solution, but the correlations used to model turbulence are at a low level. The CFD code can therefore resolve smaller scale flow processes. The development of a 3-D coupling method was carried out with the intention of improving predictive capabilities of transport properties in the downcomer and lower plenum regions of an RPV in reactor safety calculations. These regions are responsible for the multi-dimensional mixing effects that determine the distribution at the core inlet of quantities with reactivity implications, such as fluid temperature and dissolved neutron absorber concentration.

Modelling spatiotemporal change using multidimensional arrays Meng

NASA Astrophysics Data System (ADS)

Lu, Meng; Appel, Marius; Pebesma, Edzer

2017-04-01

The large variety of remote sensors, model simulations, and in-situ records provide great opportunities to model environmental change. The massive amount of high-dimensional data calls for methods to integrate data from various sources and to analyse spatiotemporal and thematic information jointly. An array is a collection of elements ordered and indexed in arbitrary dimensions, which naturally represent spatiotemporal phenomena that are identified by their geographic locations and recording time. In addition, array regridding (e.g., resampling, down-/up-scaling), dimension reduction, and spatiotemporal statistical algorithms are readily applicable to arrays. However, the role of arrays in big geoscientific data analysis has not been systematically studied: How can arrays discretise continuous spatiotemporal phenomena? How can arrays facilitate the extraction of multidimensional information? How can arrays provide a clean, scalable and reproducible change modelling process that is communicable between mathematicians, computer scientist, Earth system scientist and stakeholders? This study emphasises on detecting spatiotemporal change using satellite image time series. Current change detection methods using satellite image time series commonly analyse data in separate steps: 1) forming a vegetation index, 2) conducting time series analysis on each pixel, and 3) post-processing and mapping time series analysis results, which does not consider spatiotemporal correlations and ignores much of the spectral information. Multidimensional information can be better extracted by jointly considering spatial, spectral, and temporal information. To approach this goal, we use principal component analysis to extract multispectral information and spatial autoregressive models to account for spatial correlation in residual based time series structural change modelling. We also discuss the potential of multivariate non-parametric time series structural change methods, hierarchical modelling, and extreme event detection methods to model spatiotemporal change. We show how array operations can facilitate expressing these methods, and how the open-source array data management and analytics software SciDB and R can be used to scale the process and make it easily reproducible.

Nuclear Forensic Inferences Using Iterative Multidimensional Statistics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robel, M; Kristo, M J; Heller, M A

2009-06-09

Nuclear forensics involves the analysis of interdicted nuclear material for specific material characteristics (referred to as 'signatures') that imply specific geographical locations, production processes, culprit intentions, etc. Predictive signatures rely on expert knowledge of physics, chemistry, and engineering to develop inferences from these material characteristics. Comparative signatures, on the other hand, rely on comparison of the material characteristics of the interdicted sample (the 'questioned sample' in FBI parlance) with those of a set of known samples. In the ideal case, the set of known samples would be a comprehensive nuclear forensics database, a database which does not currently exist. Inmore » fact, our ability to analyze interdicted samples and produce an extensive list of precise materials characteristics far exceeds our ability to interpret the results. Therefore, as we seek to develop the extensive databases necessary for nuclear forensics, we must also develop the methods necessary to produce the necessary inferences from comparison of our analytical results with these large, multidimensional sets of data. In the work reported here, we used a large, multidimensional dataset of results from quality control analyses of uranium ore concentrate (UOC, sometimes called 'yellowcake'). We have found that traditional multidimensional techniques, such as principal components analysis (PCA), are especially useful for understanding such datasets and drawing relevant conclusions. In particular, we have developed an iterative partial least squares-discriminant analysis (PLS-DA) procedure that has proven especially adept at identifying the production location of unknown UOC samples. By removing classes which fell far outside the initial decision boundary, and then rebuilding the PLS-DA model, we have consistently produced better and more definitive attributions than with a single pass classification approach. Performance of the iterative PLS-DA method compared favorably to that of classification and regression tree (CART) and k nearest neighbor (KNN) algorithms, with the best combination of accuracy and robustness, as tested by classifying samples measured independently in our laboratories against the vendor QC based reference set.« less

[Enzyme kinetic glucose determination by the glucose dehydrogenase method. Enzyme kinetic substrate determination using competitive inhibitors, II (author's transl)].

PubMed

Müller-Matthesius, R

1975-05-01

The sensitivity of enzyme kinetic substrate determinations can be improved with the aid of competitive inhibitors. As an example, the determination of glucose dehydrogenase in the presence of potassium thiocyanate is described. The method has the advantage of rapid operation with satisfactory precision.

Models of multidimensional discrete distribution of probabilities of random variables in information systems

NASA Astrophysics Data System (ADS)

Gromov, Yu Yu; Minin, Yu V.; Ivanova, O. G.; Morozova, O. N.

2018-03-01

Multidimensional discrete distributions of probabilities of independent random values were received. Their one-dimensional distribution is widely used in probability theory. Producing functions of those multidimensional distributions were also received.

Validity and reliability of the multidimensional assessment of fatigue scale in Iranian patients with relapsing-remitting subtype of multiple sclerosis.

PubMed

Behrangrad, Shabnam; Kordi Yoosefinejad, Amin

2018-03-01

The purpose of this study is to investigate the validity and reliability of the Persian version of the Multidimensional Assessment of Fatigue Scale (MAFS) in an Iranian population with multiple sclerosis. A self-reported survey on fatigue including the MAFS, Fatigue Impact Scale and demographic measures was completed by 130 patients with multiple sclerosis and 60 healthy persons sampled with a convenience method. Test-retest reliability and validity were evaluated 3 days apart. Construct validity of the MAFS was assessed with the Fatigue Impact Scale. The MAFS had high internal consistency (Cronbach's alpha >0.9) and 3-d test-retest reliability (intraclass correlation coefficient = 0.99). Correlation between the Fatigue Impact Scale and MAFS was high (r = 0.99). Correlation between MAFS scores and the Expanded Disability Status Scale was also strong (r = 0.85). Questionnaire items showed acceptable item-scale correlation (0.968-0.993). The Persian version of the MAFS appears to be a valid and reliable questionnaire. It is an appropriate short multidimensional instrument to assess fatigue in patients with multiple sclerosis in clinical practice and research. Implications for Rehabilitation The Persian version of Multidimensional Assessment of Fatigue is a valid and reliable instrument for the assessment and monitoring the fatigue in Persian-language patients with multiple sclerosis. It is very easy to administer and a time efficient scale in comparison to other instruments evaluating fatigue in patients with multiple sclerosis.

Advances in quantum and molecular mechanical (QM/MM) simulations for organic and enzymatic reactions.

PubMed

Acevedo, Orlando; Jorgensen, William L

2010-01-19

Application of combined quantum and molecular mechanical (QM/MM) methods focuses on predicting activation barriers and the structures of stationary points for organic and enzymatic reactions. Characterization of the factors that stabilize transition structures in solution and in enzyme active sites provides a basis for design and optimization of catalysts. Continued technological advances allowed for expansion from prototypical cases to mechanistic studies featuring detailed enzyme and condensed-phase environments with full integration of the QM calculations and configurational sampling. This required improved algorithms featuring fast QM methods, advances in computing changes in free energies including free-energy perturbation (FEP) calculations, and enhanced configurational sampling. In particular, the present Account highlights development of the PDDG/PM3 semi-empirical QM method, computation of multi-dimensional potentials of mean force (PMF), incorporation of on-the-fly QM in Monte Carlo (MC) simulations, and a polynomial quadrature method for efficient modeling of proton-transfer reactions. The utility of this QM/MM/MC/FEP methodology is illustrated for a variety of organic reactions including substitution, decarboxylation, elimination, and pericyclic reactions. A comparison to experimental kinetic results on medium effects has verified the accuracy of the QM/MM approach in the full range of solvents from hydrocarbons to water to ionic liquids. Corresponding results from ab initio and density functional theory (DFT) methods with continuum-based treatments of solvation reveal deficiencies, particularly for protic solvents. Also summarized in this Account are three specific QM/MM applications to biomolecular systems: (1) a recent study that clarified the mechanism for the reaction of 2-pyrone derivatives catalyzed by macrophomate synthase as a tandem Michael-aldol sequence rather than a Diels-Alder reaction, (2) elucidation of the mechanism of action of fatty acid amide hydrolase (FAAH), an unusual Ser-Ser-Lys proteolytic enzyme, and (3) the construction of enzymes for Kemp elimination of 5-nitrobenzisoxazole that highlights the utility of QM/MM in the design of artificial enzymes.

A Generic multi-dimensional feature extraction method using multiobjective genetic programming.

PubMed

Zhang, Yang; Rockett, Peter I

2009-01-01

In this paper, we present a generic feature extraction method for pattern classification using multiobjective genetic programming. This not only evolves the (near-)optimal set of mappings from a pattern space to a multi-dimensional decision space, but also simultaneously optimizes the dimensionality of that decision space. The presented framework evolves vector-to-vector feature extractors that maximize class separability. We demonstrate the efficacy of our approach by making statistically-founded comparisons with a wide variety of established classifier paradigms over a range of datasets and find that for most of the pairwise comparisons, our evolutionary method delivers statistically smaller misclassification errors. At very worst, our method displays no statistical difference in a few pairwise comparisons with established classifier/dataset combinations; crucially, none of the misclassification results produced by our method is worse than any comparator classifier. Although principally focused on feature extraction, feature selection is also performed as an implicit side effect; we show that both feature extraction and selection are important to the success of our technique. The presented method has the practical consequence of obviating the need to exhaustively evaluate a large family of conventional classifiers when faced with a new pattern recognition problem in order to attain a good classification accuracy.

Recent developments in multidimensional transport methods for the APOLLO 2 lattice code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zmijarevic, I.; Sanchez, R.

1995-12-31

A usual method of preparation of homogenized cross sections for reactor coarse-mesh calculations is based on two-dimensional multigroup transport treatment of an assembly together with an appropriate leakage model and reaction-rate-preserving homogenization technique. The actual generation of assembly spectrum codes based on collision probability methods is capable of treating complex geometries (i.e., irregular meshes of arbitrary shape), thus avoiding the modeling error that was introduced in codes with traditional tracking routines. The power and architecture of current computers allow the treatment of spatial domains comprising several mutually interacting assemblies using fine multigroup structure and retaining all geometric details of interest.more » Increasing safety requirements demand detailed two- and three-dimensional calculations for very heterogeneous problems such as control rod positioning, broken Pyrex rods, irregular compacting of mixed- oxide (MOX) pellets at an MOX-UO{sub 2} interface, and many others. An effort has been made to include accurate multi- dimensional transport methods in the APOLLO 2 lattice code. These include extension to three-dimensional axially symmetric geometries of the general-geometry collision probability module TDT and the development of new two- and three-dimensional characteristics methods for regular Cartesian meshes. In this paper we discuss the main features of recently developed multidimensional methods that are currently being tested.« less

Octahedral Tin Dioxide Nanocrystals Anchored on Vertically Aligned Carbon Aerogels as High Capacity Anode Materials for Lithium-Ion Batteries.

PubMed

Liu, Mingkai; Liu, Yuqing; Zhang, Yuting; Li, Yiliao; Zhang, Peng; Yan, Yan; Liu, Tianxi

2016-08-11

A novel binder-free graphene - carbon nanotubes - SnO2 (GCNT-SnO2) aerogel with vertically aligned pores was prepared via a simple and efficient directional freezing method. SnO2 octahedrons exposed of {221} high energy facets were uniformly distributed and tightly anchored on multidimensional graphene/carbon nanotube (GCNT) composites. Vertically aligned pores can effectively prevent the emersion of "closed" pores which cannot load the active SnO2 nanoparticles, further ensure quick immersion of electrolyte throughout the aerogel, and can largely shorten the transport distance between lithium ions and active sites of SnO2. Especially, excellent electrical conductivity of GCNT-SnO2 aerogel was achieved as a result of good interconnected networks of graphene and CNTs. Furthermore, meso- and macroporous structures with large surface area created by the vertically aligned pores can provide great benefit to the favorable transport kinetics for both lithium ion and electrons and afford sufficient space for volume expansion of SnO2. Due to the well-designed architecture of GCNT-SnO2 aerogel, a high specific capacity of 1190 mAh/g with good long-term cycling stability up to 1000 times was achieved. This work provides a promising strategy for preparing free-standing and binder-free active electrode materials with high performance for lithium ion batteries and other energy storage devices.

Octahedral Tin Dioxide Nanocrystals Anchored on Vertically Aligned Carbon Aerogels as High Capacity Anode Materials for Lithium-Ion Batteries

NASA Astrophysics Data System (ADS)

Liu, Mingkai; Liu, Yuqing; Zhang, Yuting; Li, Yiliao; Zhang, Peng; Yan, Yan; Liu, Tianxi

2016-08-01

A novel binder-free graphene - carbon nanotubes - SnO2 (GCNT-SnO2) aerogel with vertically aligned pores was prepared via a simple and efficient directional freezing method. SnO2 octahedrons exposed of {221} high energy facets were uniformly distributed and tightly anchored on multidimensional graphene/carbon nanotube (GCNT) composites. Vertically aligned pores can effectively prevent the emersion of “closed” pores which cannot load the active SnO2 nanoparticles, further ensure quick immersion of electrolyte throughout the aerogel, and can largely shorten the transport distance between lithium ions and active sites of SnO2. Especially, excellent electrical conductivity of GCNT-SnO2 aerogel was achieved as a result of good interconnected networks of graphene and CNTs. Furthermore, meso- and macroporous structures with large surface area created by the vertically aligned pores can provide great benefit to the favorable transport kinetics for both lithium ion and electrons and afford sufficient space for volume expansion of SnO2. Due to the well-designed architecture of GCNT-SnO2 aerogel, a high specific capacity of 1190 mAh/g with good long-term cycling stability up to 1000 times was achieved. This work provides a promising strategy for preparing free-standing and binder-free active electrode materials with high performance for lithium ion batteries and other energy storage devices.

Persistent Topology and Metastable State in Conformational Dynamics

PubMed Central

Chang, Huang-Wei; Bacallado, Sergio; Pande, Vijay S.; Carlsson, Gunnar E.

2013-01-01

The large amount of molecular dynamics simulation data produced by modern computational models brings big opportunities and challenges to researchers. Clustering algorithms play an important role in understanding biomolecular kinetics from the simulation data, especially under the Markov state model framework. However, the ruggedness of the free energy landscape in a biomolecular system makes common clustering algorithms very sensitive to perturbations of the data. Here, we introduce a data-exploratory tool which provides an overview of the clustering structure under different parameters. The proposed Multi-Persistent Clustering analysis combines insights from recent studies on the dynamics of systems with dominant metastable states with the concept of multi-dimensional persistence in computational topology. We propose to explore the clustering structure of the data based on its persistence on scale and density. The analysis provides a systematic way to discover clusters that are robust to perturbations of the data. The dominant states of the system can be chosen with confidence. For the clusters on the borderline, the user can choose to do more simulation or make a decision based on their structural characteristics. Furthermore, our multi-resolution analysis gives users information about the relative potential of the clusters and their hierarchical relationship. The effectiveness of the proposed method is illustrated in three biomolecules: alanine dipeptide, Villin headpiece, and the FiP35 WW domain. PMID:23565139

Extraction kinetic modelling of total polyphenols and total anthocyanins from saffron floral bio-residues: Comparison of extraction methods.

PubMed

Da Porto, Carla; Natolino, Andrea

2018-08-30

Analysis of the extraction kinetic modelling for natural compounds is essential for industrial application. The second order rate model was applied to estimate the extraction kinetics of conventional solid-liquid extraction (CSLE), ultrasound-assisted extraction (UAE) and microwave-assisted extraction (MAE) of total polyphenols (TPC) from saffron floral bio-residues at different solid-to-liquid ratios (R S/L )(1:10, 1:20, 1:30, 1:50 g ml -1 ), ethanol 59% as solvent and 66 °C temperature. The optimum solid-to-liquid ratios for TPC kinetics were 1:20 for CLSE, 1:30 for UAE and 1:50 for MAE. The kinetics of total anthocyanins (TA) and antioxidant activity (AA) were investigated for the optimum R S/L for each method. The results showed a good prediction of the model for extraction kinetics in all experiments (R 2  > 0.99; NRMS 0.65-3.35%). The kinetic parameters were calculated and discussed. UAE, compared with the other methods, had the greater efficiency for TPC, TA and AA. Copyright © 2018 Elsevier Ltd. All rights reserved.

Validation of Bayesian analysis of compartmental kinetic models in medical imaging.

PubMed

Sitek, Arkadiusz; Li, Quanzheng; El Fakhri, Georges; Alpert, Nathaniel M

2016-10-01

Kinetic compartmental analysis is frequently used to compute physiologically relevant quantitative values from time series of images. In this paper, a new approach based on Bayesian analysis to obtain information about these parameters is presented and validated. The closed-form of the posterior distribution of kinetic parameters is derived with a hierarchical prior to model the standard deviation of normally distributed noise. Markov chain Monte Carlo methods are used for numerical estimation of the posterior distribution. Computer simulations of the kinetics of F18-fluorodeoxyglucose (FDG) are used to demonstrate drawing statistical inferences about kinetic parameters and to validate the theory and implementation. Additionally, point estimates of kinetic parameters and covariance of those estimates are determined using the classical non-linear least squares approach. Posteriors obtained using methods proposed in this work are accurate as no significant deviation from the expected shape of the posterior was found (one-sided P>0.08). It is demonstrated that the results obtained by the standard non-linear least-square methods fail to provide accurate estimation of uncertainty for the same data set (P<0.0001). The results of this work validate new methods for a computer simulations of FDG kinetics. Results show that in situations where the classical approach fails in accurate estimation of uncertainty, Bayesian estimation provides an accurate information about the uncertainties in the parameters. Although a particular example of FDG kinetics was used in the paper, the methods can be extended for different pharmaceuticals and imaging modalities. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Multidimensional Knowledge Structures.

ERIC Educational Resources Information Center

Schuh, Kathy L.

Multidimensional knowledge structures, described from a constructivist perspective and aligned with the "Mind as Rhizome" metaphor, provide support for constructivist learning strategies. This qualitative study was conducted to seek empirical support for a description of multidimensional knowledge structures, focusing on the…

Multidimensional quantum entanglement with large-scale integrated optics.

PubMed

Wang, Jianwei; Paesani, Stefano; Ding, Yunhong; Santagati, Raffaele; Skrzypczyk, Paul; Salavrakos, Alexia; Tura, Jordi; Augusiak, Remigiusz; Mančinska, Laura; Bacco, Davide; Bonneau, Damien; Silverstone, Joshua W; Gong, Qihuang; Acín, Antonio; Rottwitt, Karsten; Oxenløwe, Leif K; O'Brien, Jeremy L; Laing, Anthony; Thompson, Mark G

2018-04-20

The ability to control multidimensional quantum systems is central to the development of advanced quantum technologies. We demonstrate a multidimensional integrated quantum photonic platform able to generate, control, and analyze high-dimensional entanglement. A programmable bipartite entangled system is realized with dimensions up to 15 × 15 on a large-scale silicon photonics quantum circuit. The device integrates more than 550 photonic components on a single chip, including 16 identical photon-pair sources. We verify the high precision, generality, and controllability of our multidimensional technology, and further exploit these abilities to demonstrate previously unexplored quantum applications, such as quantum randomness expansion and self-testing on multidimensional states. Our work provides an experimental platform for the development of multidimensional quantum technologies. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Fundamental electrode kinetics

NASA Technical Reports Server (NTRS)

Elder, J. P.

1968-01-01

Report presents the fundamentals of electrode kinetics and the methods used in evaluating the characteristic parameters of rapid-charge transfer processes at electrode-electrolyte interfaces. The concept of electrode kinetics is outlined, followed by the principles underlying the experimental techniques for the investigation of electrode kinetics.

A WENO-Limited, ADER-DT, Finite-Volume Scheme for Efficient, Robust, and Communication-Avoiding Multi-Dimensional Transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Norman, Matthew R

2014-01-01

The novel ADER-DT time discretization is applied to two-dimensional transport in a quadrature-free, WENO- and FCT-limited, Finite-Volume context. Emphasis is placed on (1) the serial and parallel computational properties of ADER-DT and this framework and (2) the flexibility of ADER-DT and this framework in efficiently balancing accuracy with other constraints important to transport applications. This study demonstrates a range of choices for the user when approaching their specific application while maintaining good parallel properties. In this method, genuine multi-dimensionality, single-step and single-stage time stepping, strict positivity, and a flexible range of limiting are all achieved with only one parallel synchronizationmore » and data exchange per time step. In terms of parallel data transfers per simulated time interval, this improves upon multi-stage time stepping and post-hoc filtering techniques such as hyperdiffusion. This method is evaluated with standard transport test cases over a range of limiting options to demonstrate quantitatively and qualitatively what a user should expect when employing this method in their application.« less

Bayesian nonparametric clustering in phylogenetics: modeling antigenic evolution in influenza.

PubMed

Cybis, Gabriela B; Sinsheimer, Janet S; Bedford, Trevor; Rambaut, Andrew; Lemey, Philippe; Suchard, Marc A

2018-01-30

Influenza is responsible for up to 500,000 deaths every year, and antigenic variability represents much of its epidemiological burden. To visualize antigenic differences across many viral strains, antigenic cartography methods use multidimensional scaling on binding assay data to map influenza antigenicity onto a low-dimensional space. Analysis of such assay data ideally leads to natural clustering of influenza strains of similar antigenicity that correlate with sequence evolution. To understand the dynamics of these antigenic groups, we present a framework that jointly models genetic and antigenic evolution by combining multidimensional scaling of binding assay data, Bayesian phylogenetic machinery and nonparametric clustering methods. We propose a phylogenetic Chinese restaurant process that extends the current process to incorporate the phylogenetic dependency structure between strains in the modeling of antigenic clusters. With this method, we are able to use the genetic information to better understand the evolution of antigenicity throughout epidemics, as shown in applications of this model to H1N1 influenza. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Occurrence of dead core in catalytic particles containing immobilized enzymes: analysis for the Michaelis-Menten kinetics and assessment of numerical methods.

PubMed

Pereira, Félix Monteiro; Oliveira, Samuel Conceição

2016-11-01

In this article, the occurrence of dead core in catalytic particles containing immobilized enzymes is analyzed for the Michaelis-Menten kinetics. An assessment of numerical methods is performed to solve the boundary value problem generated by the mathematical modeling of diffusion and reaction processes under steady state and isothermal conditions. Two classes of numerical methods were employed: shooting and collocation. The shooting method used the ode function from Scilab software. The collocation methods included: that implemented by the bvode function of Scilab, the orthogonal collocation, and the orthogonal collocation on finite elements. The methods were validated for simplified forms of the Michaelis-Menten equation (zero-order and first-order kinetics), for which analytical solutions are available. Among the methods covered in this article, the orthogonal collocation on finite elements proved to be the most robust and efficient method to solve the boundary value problem concerning Michaelis-Menten kinetics. For this enzyme kinetics, it was found that the dead core can occur when verified certain conditions of diffusion-reaction within the catalytic particle. The application of the concepts and methods presented in this study will allow for a more generalized analysis and more accurate designs of heterogeneous enzymatic reactors.

Peptide kinetics from picoseconds to microseconds using boxed molecular dynamics: Power law rate coefficients in cyclisation reactions

NASA Astrophysics Data System (ADS)

Shalashilin, Dmitrii V.; Beddard, Godfrey S.; Paci, Emanuele; Glowacki, David R.

2012-10-01

Molecular dynamics (MD) methods are increasingly widespread, but simulation of rare events in complex molecular systems remains a challenge. We recently introduced the boxed molecular dynamics (BXD) method, which accelerates rare events, and simultaneously provides both kinetic and thermodynamic information. We illustrate how the BXD method may be used to obtain high-resolution kinetic data from explicit MD simulations, spanning picoseconds to microseconds. The method is applied to investigate the loop formation dynamics and kinetics of cyclisation for a range of polypeptides, and recovers a power law dependence of the instantaneous rate coefficient over six orders of magnitude in time, in good agreement with experimental observations. Analysis of our BXD results shows that this power law behaviour arises when there is a broad and nearly uniform spectrum of reaction rate coefficients. For the systems investigated in this work, where the free energy surfaces have relatively small barriers, the kinetics is very sensitive to the initial conditions: strongly non-equilibrium conditions give rise to power law kinetics, while equilibrium initial conditions result in a rate coefficient with only a weak dependence on time. These results suggest that BXD may offer us a powerful and general algorithm for describing kinetics and thermodynamics in chemical and biochemical systems.

Comparison of Factor Simplicity Indices for Dichotomous Data: DETECT R, Bentler's Simplicity Index, and the Loading Simplicity Index

ERIC Educational Resources Information Center

Finch, Holmes; Stage, Alan Kirk; Monahan, Patrick

2008-01-01

A primary assumption underlying several of the common methods for modeling item response data is unidimensionality, that is, test items tap into only one latent trait. This assumption can be assessed several ways, using nonlinear factor analysis and DETECT, a method based on the item conditional covariances. When multidimensionality is identified,…

The method of trend analysis of parameters time series of gas-turbine engine state

NASA Astrophysics Data System (ADS)

Hvozdeva, I.; Myrhorod, V.; Derenh, Y.

2017-10-01

This research substantiates an approach to interval estimation of time series trend component. The well-known methods of spectral and trend analysis are used for multidimensional data arrays. The interval estimation of trend component is proposed for the time series whose autocorrelation matrix possesses a prevailing eigenvalue. The properties of time series autocorrelation matrix are identified.

Modeling Local Item Dependence Due to Common Test Format with a Multidimensional Rasch Model

ERIC Educational Resources Information Center

Baghaei, Purya; Aryadoust, Vahid

2015-01-01

Research shows that test method can exert a significant impact on test takers' performance and thereby contaminate test scores. We argue that common test method can exert the same effect as common stimuli and violate the conditional independence assumption of item response theory models because, in general, subsets of items which have a shared…

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1985-01-01

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

A Simulation Study on Methods of Correcting for the Effects of Extreme Response Style

ERIC Educational Resources Information Center

Wetzel, Eunike; Böhnke, Jan R.; Rose, Norman

2016-01-01

The impact of response styles such as extreme response style (ERS) on trait estimation has long been a matter of concern to researchers and practitioners. This simulation study investigated three methods that have been proposed for the correction of trait estimates for ERS effects: (a) mixed Rasch models, (b) multidimensional item response models,…

Fluorescence Intrinsic Characterization of Excitation-Emission Matrix Using Multi-Dimensional Ensemble Empirical Mode Decomposition

PubMed Central

Chang, Chi-Ying; Chang, Chia-Chi; Hsiao, Tzu-Chien

2013-01-01

Excitation-emission matrix (EEM) fluorescence spectroscopy is a noninvasive method for tissue diagnosis and has become important in clinical use. However, the intrinsic characterization of EEM fluorescence remains unclear. Photobleaching and the complexity of the chemical compounds make it difficult to distinguish individual compounds due to overlapping features. Conventional studies use principal component analysis (PCA) for EEM fluorescence analysis, and the relationship between the EEM features extracted by PCA and diseases has been examined. The spectral features of different tissue constituents are not fully separable or clearly defined. Recently, a non-stationary method called multi-dimensional ensemble empirical mode decomposition (MEEMD) was introduced; this method can extract the intrinsic oscillations on multiple spatial scales without loss of information. The aim of this study was to propose a fluorescence spectroscopy system for EEM measurements and to describe a method for extracting the intrinsic characteristics of EEM by MEEMD. The results indicate that, although PCA provides the principal factor for the spectral features associated with chemical compounds, MEEMD can provide additional intrinsic features with more reliable mapping of the chemical compounds. MEEMD has the potential to extract intrinsic fluorescence features and improve the detection of biochemical changes. PMID:24240806

Multidimensional Perfectionism and the Self

ERIC Educational Resources Information Center

Ward, Andrew M.; Ashby, Jeffrey S.

2008-01-01

This study examined multidimensional perfectionism and self-development. Two hundred seventy-one undergraduates completed a measure of multidimensional perfectionism and two Kohutian measures designed to measure aspects of self-development including social connectedness, social assurance, goal instability (idealization), and grandiosity. The…

A BAYESIAN METHOD OF ESTIMATING KINETIC PARAMETERS FOR THE INACTIVATION OF CRYPTOSPORIDIUM PARVUM OOCYSTS WITH CHLORINE DIOXIDE AND OZONE

EPA Science Inventory

The main objective of this paper is to use Bayesian methods to estimate the kinetic parameters for the inactivation kinetics of Cryptosporidium parvum oocysts with chlorine dioxide or ozone which are characterized by the delayed Chick-Watson model, i.e., a lag phase or shoulder f...

Measurement of Enzyme Kinetics by Use of a Blood Glucometer: Hydrolysis of Sucrose and Lactose

ERIC Educational Resources Information Center

Heinzerling, Peter; Schrader, Frank; Schanze, Sascha

2012-01-01

An alternative analytical method for measuring the kinetic parameters of the enzymes invertase and lactase is described. Invertase hydrolyzes sucrose to glucose and fructose and lactase hydrolyzes lactose to glucose and galactose. In most enzyme kinetics studies, photometric methods or test strips are used to quantify the derivates of the…

Tomographic Image Compression Using Multidimensional Transforms.

ERIC Educational Resources Information Center

Villasenor, John D.

1994-01-01

Describes a method for compressing tomographic images obtained using Positron Emission Tomography (PET) and Magnetic Resonance (MR) by applying transform compression using all available dimensions. This takes maximum advantage of redundancy of the data, allowing significant increases in compression efficiency and performance. (13 references) (KRN)

Chemical space visualization: transforming multidimensional chemical spaces into similarity-based molecular networks.

PubMed

de la Vega de León, Antonio; Bajorath, Jürgen

2016-09-01

The concept of chemical space is of fundamental relevance for medicinal chemistry and chemical informatics. Multidimensional chemical space representations are coordinate-based. Chemical space networks (CSNs) have been introduced as a coordinate-free representation. A computational approach is presented for the transformation of multidimensional chemical space into CSNs. The design of transformation CSNs (TRANS-CSNs) is based upon a similarity function that directly reflects distance relationships in original multidimensional space. TRANS-CSNs provide an immediate visualization of coordinate-based chemical space and do not require the use of dimensionality reduction techniques. At low network density, TRANS-CSNs are readily interpretable and make it possible to evaluate structure-activity relationship information originating from multidimensional chemical space.

A cross-diffusion system derived from a Fokker-Planck equation with partial averaging

NASA Astrophysics Data System (ADS)

Jüngel, Ansgar; Zamponi, Nicola

2017-02-01

A cross-diffusion system for two components with a Laplacian structure is analyzed on the multi-dimensional torus. This system, which was recently suggested by P.-L. Lions, is formally derived from a Fokker-Planck equation for the probability density associated with a multi-dimensional Itō process, assuming that the diffusion coefficients depend on partial averages of the probability density with exponential weights. A main feature is that the diffusion matrix of the limiting cross-diffusion system is generally neither symmetric nor positive definite, but its structure allows for the use of entropy methods. The global-in-time existence of positive weak solutions is proved and, under a simplifying assumption, the large-time asymptotics is investigated.

Data matching for free-surface multiple attenuation by multidimensional deconvolution

NASA Astrophysics Data System (ADS)

van der Neut, Joost; Frijlink, Martijn; van Borselen, Roald

2012-09-01

A common strategy for surface-related multiple elimination of seismic data is to predict multiples by a convolutional model and subtract these adaptively from the input gathers. Problems can be posed by interfering multiples and primaries. Removing multiples by multidimensional deconvolution (MDD) (inversion) does not suffer from these problems. However, this approach requires data to be consistent, which is often not the case, especially not at interpolated near-offsets. A novel method is proposed to improve data consistency prior to inversion. This is done by backpropagating first-order multiples with a time-gated reference primary event and matching these with early primaries in the input gather. After data matching, multiple elimination by MDD can be applied with a deterministic inversion scheme.

Improved Modeling of Finite-Rate Turbulent Combustion Processes in Research Combustors

NASA Technical Reports Server (NTRS)

VanOverbeke, Thomas J.

1998-01-01

The objective of this thesis is to further develop and test a stochastic model of turbulent combustion in recirculating flows. There is a requirement to increase the accuracy of multi-dimensional combustion predictions. As turbulence affects reaction rates, this interaction must be more accurately evaluated. In this work a more physically correct way of handling the interaction of turbulence on combustion is further developed and tested. As turbulence involves randomness, stochastic modeling is used. Averaged values such as temperature and species concentration are found by integrating the probability density function (pdf) over the range of the scalar. The model in this work does not assume the pdf type, but solves for the evolution of the pdf using the Monte Carlo solution technique. The model is further developed by including a more robust reaction solver, by using accurate thermodynamics and by more accurate transport elements. The stochastic method is used with Semi-Implicit Method for Pressure-Linked Equations. The SIMPLE method is used to solve for velocity, pressure, turbulent kinetic energy and dissipation. The pdf solver solves for temperature and species concentration. Thus, the method is partially familiar to combustor engineers. The method is compared to benchmark experimental data and baseline calculations. The baseline method was tested on isothermal flows, evaporating sprays and combusting sprays. Pdf and baseline predictions were performed for three diffusion flames and one premixed flame. The pdf method predicted lower combustion rates than the baseline method in agreement with the data, except for the premixed flame. The baseline and stochastic predictions bounded the experimental data for the premixed flame. The use of a continuous mixing model or relax to mean mixing model had little effect on the prediction of average temperature. Two grids were used in a hydrogen diffusion flame simulation. Grid density did not effect the predictions except for peak temperature and tangential velocity. The hybrid pdf method did take longer and required more memory, but has a theoretical basis to extend to many reaction steps which cannot be said of current turbulent combustion models.

Scientific Visualization and Simulation for Multi-dimensional Marine Environment Data

NASA Astrophysics Data System (ADS)

Su, T.; Liu, H.; Wang, W.; Song, Z.; Jia, Z.

2017-12-01

As higher attention on the ocean and rapid development of marine detection, there are increasingly demands for realistic simulation and interactive visualization of marine environment in real time. Based on advanced technology such as GPU rendering, CUDA parallel computing and rapid grid oriented strategy, a series of efficient and high-quality visualization methods, which can deal with large-scale and multi-dimensional marine data in different environmental circumstances, has been proposed in this paper. Firstly, a high-quality seawater simulation is realized by FFT algorithm, bump mapping and texture animation technology. Secondly, large-scale multi-dimensional marine hydrological environmental data is virtualized by 3d interactive technologies and volume rendering techniques. Thirdly, seabed terrain data is simulated with improved Delaunay algorithm, surface reconstruction algorithm, dynamic LOD algorithm and GPU programming techniques. Fourthly, seamless modelling in real time for both ocean and land based on digital globe is achieved by the WebGL technique to meet the requirement of web-based application. The experiments suggest that these methods can not only have a satisfying marine environment simulation effect, but also meet the rendering requirements of global multi-dimension marine data. Additionally, a simulation system for underwater oil spill is established by OSG 3D-rendering engine. It is integrated with the marine visualization method mentioned above, which shows movement processes, physical parameters, current velocity and direction for different types of deep water oil spill particle (oil spill particles, hydrates particles, gas particles, etc.) dynamically and simultaneously in multi-dimension. With such application, valuable reference and decision-making information can be provided for understanding the progress of oil spill in deep water, which is helpful for ocean disaster forecasting, warning and emergency response.

Highly Reproducible Label Free Quantitative Proteomic Analysis of RNA Polymerase Complexes*

PubMed Central

Mosley, Amber L.; Sardiu, Mihaela E.; Pattenden, Samantha G.; Workman, Jerry L.; Florens, Laurence; Washburn, Michael P.

2011-01-01

The use of quantitative proteomics methods to study protein complexes has the potential to provide in-depth information on the abundance of different protein components as well as their modification state in various cellular conditions. To interrogate protein complex quantitation using shotgun proteomic methods, we have focused on the analysis of protein complexes using label-free multidimensional protein identification technology and studied the reproducibility of biological replicates. For these studies, we focused on three highly related and essential multi-protein enzymes, RNA polymerase I, II, and III from Saccharomyces cerevisiae. We found that label-free quantitation using spectral counting is highly reproducible at the protein and peptide level when analyzing RNA polymerase I, II, and III. In addition, we show that peptide sampling does not follow a random sampling model, and we show the need for advanced computational models to predict peptide detection probabilities. In order to address these issues, we used the APEX protocol to model the expected peptide detectability based on whole cell lysate acquired using the same multidimensional protein identification technology analysis used for the protein complexes. Neither method was able to predict the peptide sampling levels that we observed using replicate multidimensional protein identification technology analyses. In addition to the analysis of the RNA polymerase complexes, our analysis provides quantitative information about several RNAP associated proteins including the RNAPII elongation factor complexes DSIF and TFIIF. Our data shows that DSIF and TFIIF are the most highly enriched RNAP accessory factors in Rpb3-TAP purifications and demonstrate our ability to measure low level associated protein abundance across biological replicates. In addition, our quantitative data supports a model in which DSIF and TFIIF interact with RNAPII in a dynamic fashion in agreement with previously published reports. PMID:21048197

A study of the kinetics of isothermal nicotine desorption from silicon dioxide

NASA Astrophysics Data System (ADS)

Adnadjevic, Borivoj; Lazarevic, Natasa; Jovanovic, Jelena

2010-12-01

The isothermal kinetics of nicotine desorption from silicon dioxide (SiO 2) was investigated. The isothermal thermogravimetric curves of nicotine at temperatures of 115 °C, 130 °C and 152 °C were recorded. The kinetic parameters ( Ea, ln A) of desorption of nicotine were calculated using various methods (stationary point, model constants and differential isoconversion method). By applying the "model-fitting" method, it was found that the kinetic model of nicotine desorption from silicon dioxide was a phase boundary controlled reaction (contracting volume). The values of the kinetic parameters, Ea,α and ln Aα, complexly change with changing degree of desorption and a compensation effect exists. A new mechanism of activation for the desorption of the absorbed molecules of nicotine was suggested in agreement with model of selective energy transfer.

Multidimensional Poverty in Rural Mozambique: A New Metric for Evaluating Public Health Interventions

PubMed Central

Victor, Bart; Blevins, Meridith; Green, Ann F.; Ndatimana, Elisée; González-Calvo, Lázaro; Fischer, Edward F.; Vergara, Alfredo E.; Vermund, Sten H.; Olupona, Omo; Moon, Troy D.

2014-01-01

Background Poverty is a multidimensional phenomenon and unidimensional measurements have proven inadequate to the challenge of assessing its dynamics. Dynamics between poverty and public health intervention is among the most difficult yet important problems faced in development. We sought to demonstrate how multidimensional poverty measures can be utilized in the evaluation of public health interventions; and to create geospatial maps of poverty deprivation to aid implementers in prioritizing program planning. Methods Survey teams interviewed a representative sample of 3,749 female heads of household in 259 enumeration areas across Zambézia in August-September 2010. We estimated a multidimensional poverty index, which can be disaggregated into context-specific indicators. We produced an MPI comprised of 3 dimensions and 11 weighted indicators selected from the survey. Households were identified as “poor” if were deprived in >33% of indicators. Our MPI is an adjusted headcount, calculated by multiplying the proportion identified as poor (headcount) and the poverty gap (average deprivation). Geospatial visualizations of poverty deprivation were created as a contextual baseline for future evaluation. Results In our rural (96%) and urban (4%) interviewees, the 33% deprivation cut-off suggested 58.2% of households were poor (29.3% of urban vs. 59.5% of rural). Among the poor, households experienced an average deprivation of 46%; thus the MPI/adjusted headcount is 0.27 ( = 0.58×0.46). Of households where a local language was the primary language, 58.6% were considered poor versus Portuguese-speaking households where 73.5% were considered non-poor. Living standard is the dominant deprivation, followed by health, and then education. Conclusions Multidimensional poverty measurement can be integrated into program design for public health interventions, and geospatial visualization helps examine the impact of intervention deployment within the context of distinct poverty conditions. Both permit program implementers to focus resources and critically explore linkages between poverty and its social determinants, thus deriving useful findings for evidence-based planning. PMID:25268951

Kinetic Description of the Impedance Probe

NASA Astrophysics Data System (ADS)

Oberrath, Jens; Lapke, Martin; Mussenbrock, Thomas; Brinkmann, Ralf

2011-10-01

Active plasma resonance spectroscopy is a well known diagnostic method. Many concepts of this method are theoretically investigated and realized as a diagnostic tool, one of which is the impedance probe (IP). The application of such a probe in plasmas with pressures of a few Pa raises the question whether kinetic effects have to be taken into account or not. To address this question a kinetic model is necessary. A general kinetic model for an electrostatic concept of active plasma spectroscopy was presented by R.P. Brinkmann and can be used to describe the multipole resonance probe (MRP). In principle the IP is interpretable as a special case of the MRP in lower order. Thus, we are able to describe the IP by the kinetic model of the MRP. Based on this model we derive a solution to investigate the influence of kinetic effects to the resonance behavior of the IP. Active plasma resonance spectroscopy is a well known diagnostic method. Many concepts of this method are theoretically investigated and realized as a diagnostic tool, one of which is the impedance probe (IP). The application of such a probe in plasmas with pressures of a few Pa raises the question whether kinetic effects have to be taken into account or not. To address this question a kinetic model is necessary. A general kinetic model for an electrostatic concept of active plasma spectroscopy was presented by R.P. Brinkmann and can be used to describe the multipole resonance probe (MRP). In principle the IP is interpretable as a special case of the MRP in lower order. Thus, we are able to describe the IP by the kinetic model of the MRP. Based on this model we derive a solution to investigate the influence of kinetic effects to the resonance behavior of the IP. The authors acknowledge the support by the Deutsche Forschungsgemeinschaft (DFG) via the Ruhr University Research School and the Federal Ministry of Education and Research in frame of the PluTO project.

Optimization of a direct spectrophotometric method to investigate the kinetics and inhibition of sialidases

PubMed Central

2012-01-01

Backgrounds Streptococcus pneumoniae expresses three distinct sialidases, NanA, NanB, and NanC, that are believed to be key virulence factors and thus, potential important drug targets. We previously reported that the three enzymes release different products from sialosides, but could share a common catalytic mechanism before the final step of product formation. However, the kinetic investigations of the three sialidases have not been systematically done thus far, due to the lack of an easy and steady measurement of sialidase reaction rate. Results In this work, we present further kinetic characterization of pneumococcal sialidases by using a direct spectrophotometric method with the chromogenic substrate p-nitrophenyl-N-acetylneuraminic acid (p-NP-Neu5Ac). Using our assay, the measured kinetic parameters of the three purified pneumococcal sialidase, NanA, NanB and NanC, were obtained and were in perfect agreement with the previously published data. The major advantage of this alternative method resides in the direct measurement of the released product, allowing to readily determine of initial reaction rates and record complete hydrolysis time courses. Conclusion We developed an accurate, fast and sensitive spectrophotometric method to investigate the kinetics of sialidase-catalyzed reactions. This fast, sensitive, inexpensive and accurate method could benefit the study of the kinetics and inhibition of sialidases in general. PMID:23031230

Benchmarking the Multidimensional Stellar Implicit Code MUSIC

NASA Astrophysics Data System (ADS)

Goffrey, T.; Pratt, J.; Viallet, M.; Baraffe, I.; Popov, M. V.; Walder, R.; Folini, D.; Geroux, C.; Constantino, T.

2017-04-01

We present the results of a numerical benchmark study for the MUltidimensional Stellar Implicit Code (MUSIC) based on widely applicable two- and three-dimensional compressible hydrodynamics problems relevant to stellar interiors. MUSIC is an implicit large eddy simulation code that uses implicit time integration, implemented as a Jacobian-free Newton Krylov method. A physics based preconditioning technique which can be adjusted to target varying physics is used to improve the performance of the solver. The problems used for this benchmark study include the Rayleigh-Taylor and Kelvin-Helmholtz instabilities, and the decay of the Taylor-Green vortex. Additionally we show a test of hydrostatic equilibrium, in a stellar environment which is dominated by radiative effects. In this setting the flexibility of the preconditioning technique is demonstrated. This work aims to bridge the gap between the hydrodynamic test problems typically used during development of numerical methods and the complex flows of stellar interiors. A series of multidimensional tests were performed and analysed. Each of these test cases was analysed with a simple, scalar diagnostic, with the aim of enabling direct code comparisons. As the tests performed do not have analytic solutions, we verify MUSIC by comparing it to established codes including ATHENA and the PENCIL code. MUSIC is able to both reproduce behaviour from established and widely-used codes as well as results expected from theoretical predictions. This benchmarking study concludes a series of papers describing the development of the MUSIC code and provides confidence in future applications.

An introduction to multidimensional measurement using Rasch models.

PubMed

Briggs, Derek C; Wilson, Mark

2003-01-01

The act of constructing a measure requires a number of important assumptions. Principle among these assumptions is that the construct is unidimensional. In practice there are many instances when the assumption of unidimensionality does not hold, and where the application of a multidimensional measurement model is both technically appropriate and substantively advantageous. In this paper we illustrate the usefulness of a multidimensional approach to measurement with the Multidimensional Random Coefficient Multinomial Logit (MRCML) model, an extension of the unidimensional Rasch model. An empirical example is taken from a collection of embedded assessments administered to 541 students enrolled in middle school science classes with a hands-on science curriculum. Student achievement on these assessments are multidimensional in nature, but can also be treated as consecutive unidimensional estimates, or as is most common, as a composite unidimensional estimate. Structural parameters are estimated for each model using ConQuest, and model fit is compared. Student achievement in science is also compared across models. The multidimensional approach has the best fit to the data, and provides more reliable estimates of student achievement than under the consecutive unidimensional approach. Finally, at an interpretational level, the multidimensional approach may well provide richer information to the classroom teacher about the nature of student achievement.

Pseudo-second order models for the adsorption of safranin onto activated carbon: comparison of linear and non-linear regression methods.

PubMed

Kumar, K Vasanth

2007-04-02

Kinetic experiments were carried out for the sorption of safranin onto activated carbon particles. The kinetic data were fitted to pseudo-second order model of Ho, Sobkowsk and Czerwinski, Blanchard et al. and Ritchie by linear and non-linear regression methods. Non-linear method was found to be a better way of obtaining the parameters involved in the second order rate kinetic expressions. Both linear and non-linear regression showed that the Sobkowsk and Czerwinski and Ritchie's pseudo-second order models were the same. Non-linear regression analysis showed that both Blanchard et al. and Ho have similar ideas on the pseudo-second order model but with different assumptions. The best fit of experimental data in Ho's pseudo-second order expression by linear and non-linear regression method showed that Ho pseudo-second order model was a better kinetic expression when compared to other pseudo-second order kinetic expressions.

A multidimensional finite element method for CFD

NASA Technical Reports Server (NTRS)

Pepper, Darrell W.; Humphrey, Joseph W.

1991-01-01

A finite element method is used to solve the equations of motion for 2- and 3-D fluid flow. The time-dependent equations are solved explicitly using quadrilateral (2-D) and hexahedral (3-D) elements, mass lumping, and reduced integration. A Petrov-Galerkin technique is applied to the advection terms. The method requires a minimum of computational storage, executes quickly, and is scalable for execution on computer systems ranging from PCs to supercomputers.

Multi-Dimensional Analysis of Dynamic Human Information Interaction

ERIC Educational Resources Information Center

Park, Minsoo

2013-01-01

Introduction: This study aims to understand the interactions of perception, effort, emotion, time and performance during the performance of multiple information tasks using Web information technologies. Method: Twenty volunteers from a university participated in this study. Questionnaires were used to obtain general background information and…

Combining molecular fingerprints with multidimensional scaling analyses to identify the source of spilled oil from highly similar suspected oils.

PubMed

Zhou, Peiyu; Chen, Changshu; Ye, Jianjun; Shen, Wenjie; Xiong, Xiaofei; Hu, Ping; Fang, Hongda; Huang, Chuguang; Sun, Yongge

2015-04-15

Oil fingerprints have been a powerful tool widely used for determining the source of spilled oil. In most cases, this tool works well. However, it is usually difficult to identify the source if the oil spill accident occurs during offshore petroleum exploration due to the highly similar physiochemical characteristics of suspected oils from the same drilling platform. In this report, a case study from the waters of the South China Sea is presented, and multidimensional scaling analysis (MDS) is introduced to demonstrate how oil fingerprints can be combined with mathematical methods to identify the source of spilled oil from highly similar suspected sources. The results suggest that the MDS calculation based on oil fingerprints and subsequently integrated with specific biomarkers in spilled oils is the most effective method with a great potential for determining the source in terms of highly similar suspected oils. Copyright © 2015 Elsevier Ltd. All rights reserved.

Psychometric properties of the multidimensional perfectionism scale of Hewitt in a dutch-speaking sample: associations with the big five personality traits.

PubMed

De Cuyper, Kathleen; Claes, Laurence; Hermans, Dirk; Pieters, Guido; Smits, Dirk

2015-01-01

We administered the Dutch Multidimensional Perfectionism Scale of Hewitt and Flett (1991, 2004) in a large student sample (N = 959) and performed a confirmatory factor analysis to test the factorial structure proposed by the original authors. The existence of a method factor referring to the negatively keyed items in the questionnaire was investigated by including it in the tested models. Next, we investigated how the 3 perfectionism dimensions are associated with the Five-factor model (FFM) of personality. The 3-factor structure originally observed by the authors was confirmed, at least when a method factor that refers to the negatively keyed items was included in the model. Self-oriented and socially prescribed perfectionism were both distinguished by low extraversion and low emotional stability. Self-oriented perfectionism's positive relationship with both conscientiousness and openness to experience differentiated the 2 perfectionism dimensions from each other. Other-oriented perfectionism was not well-characterized by the Big Five personality traits.

Big Data and Deep data in scanning and electron microscopies: functionality from multidimensional data sets

DOE PAGES

Belianinov, Alex; Vasudevan, Rama K; Strelcov, Evgheni; ...

2015-05-13

The development of electron, and scanning probe microscopies in the second half of the twentieth century have produced spectacular images of internal structure and composition of matter with, at nanometer, molecular, and atomic resolution. Largely, this progress was enabled by computer-assisted methods of microscope operation, data acquisition and analysis. The progress in imaging technologies in the beginning of the twenty first century has opened the proverbial floodgates of high-veracity information on structure and functionality. High resolution imaging now allows information on atomic positions with picometer precision, allowing for quantitative measurements of individual bond length and angles. Functional imaging often leadsmore » to multidimensional data sets containing partial or full information on properties of interest, acquired as a function of multiple parameters (time, temperature, or other external stimuli). Here, we review several recent applications of the big and deep data analysis methods to visualize, compress, and translate this data into physically and chemically relevant information from imaging data.« less

Visual analytics of large multidimensional data using variable binned scatter plots

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Dayal, Umeshwar; Sharma, Ratnesh K.; Keim, Daniel A.; Janetzko, Halldór

2010-01-01

The scatter plot is a well-known method of visualizing pairs of two-dimensional continuous variables. Multidimensional data can be depicted in a scatter plot matrix. They are intuitive and easy-to-use, but often have a high degree of overlap which may occlude a significant portion of data. In this paper, we propose variable binned scatter plots to allow the visualization of large amounts of data without overlapping. The basic idea is to use a non-uniform (variable) binning of the x and y dimensions and plots all the data points that fall within each bin into corresponding squares. Further, we map a third attribute to color for visualizing clusters. Analysts are able to interact with individual data points for record level information. We have applied these techniques to solve real-world problems on credit card fraud and data center energy consumption to visualize their data distribution and cause-effect among multiple attributes. A comparison of our methods with two recent well-known variants of scatter plots is included.

I/O routing in a multidimensional torus network

DOEpatents

Chen, Dong; Eisley, Noel A.; Heidelberger, Philip

2017-02-07

A method, system and computer program product are disclosed for routing data packet in a computing system comprising a multidimensional torus compute node network including a multitude of compute nodes, and an I/O node network including a plurality of I/O nodes. In one embodiment, the method comprises assigning to each of the data packets a destination address identifying one of the compute nodes; providing each of the data packets with a toio value; routing the data packets through the compute node network to the destination addresses of the data packets; and when each of the data packets reaches the destination address assigned to said each data packet, routing said each data packet to one of the I/O nodes if the toio value of said each data packet is a specified value. In one embodiment, each of the data packets is also provided with an ioreturn value used to route the data packets through the compute node network.

Big Data and Deep data in scanning and electron microscopies: functionality from multidimensional data sets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Belianinov, Alex; Vasudevan, Rama K; Strelcov, Evgheni

The development of electron, and scanning probe microscopies in the second half of the twentieth century have produced spectacular images of internal structure and composition of matter with, at nanometer, molecular, and atomic resolution. Largely, this progress was enabled by computer-assisted methods of microscope operation, data acquisition and analysis. The progress in imaging technologies in the beginning of the twenty first century has opened the proverbial floodgates of high-veracity information on structure and functionality. High resolution imaging now allows information on atomic positions with picometer precision, allowing for quantitative measurements of individual bond length and angles. Functional imaging often leadsmore » to multidimensional data sets containing partial or full information on properties of interest, acquired as a function of multiple parameters (time, temperature, or other external stimuli). Here, we review several recent applications of the big and deep data analysis methods to visualize, compress, and translate this data into physically and chemically relevant information from imaging data.« less

Two-stage optical recording: photoinduced birefringence and surface-mediated bits storage in bisazo-containing copolymers towards ultrahigh data memory.

PubMed

Hu, Yanlei; Wu, Dong; Li, Jiawen; Huang, Wenhao; Chu, Jiaru

2016-10-03

Ultrahigh density data storage is in high demand in the current age of big data and thus motivates many innovative storage technologies. Femtosecond laser induced multi-dimensional optical data storage is an appealing method to fulfill the demand of ultrahigh storage capacity. Here we report a femtosecond laser induced two-stage optical storage in bisazobenzene copolymer films by manipulating the recording energies. Different mechanisms can be selected for specified memory use: two-photon isomerization (TPI) and laser induced surface deformation. Giant birefringence can be generated by TPI and brings about high signal-to-noise ratio (>20 dB) multi-dimensional reversible storage. Polarization-dependent surface deformation arises when increasing the recording energy, which not only facilitates the multi-level storage by black bits (dots), but also enhances the bits' readout signal and storing stability. This facile bits recording method, which enables completely different recording mechanisms in an identical storage medium, paves the way for sustainable big data storage.

I/O routing in a multidimensional torus network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Dong; Eisley, Noel A.; Heidelberger, Philip

A method, system and computer program product are disclosed for routing data packet in a computing system comprising a multidimensional torus compute node network including a multitude of compute nodes, and an I/O node network including a plurality of I/O nodes. In one embodiment, the method comprises assigning to each of the data packets a destination address identifying one of the compute nodes; providing each of the data packets with a toio value; routing the data packets through the compute node network to the destination addresses of the data packets; and when each of the data packets reaches the destinationmore » address assigned to said each data packet, routing said each data packet to one of the I/O nodes if the toio value of said each data packet is a specified value. In one embodiment, each of the data packets is also provided with an ioreturn value used to route the data packets through the compute node network.« less

Calculation of kinetic rate constants from thermodynamic data

NASA Technical Reports Server (NTRS)

Marek, C. John

1995-01-01

A new scheme for relating the absolute value for the kinetic rate constant k to the thermodynamic constant Kp is developed for gases. In this report the forward and reverse rate constants are individually related to the thermodynamic data. The kinetic rate constants computed from thermodynamics compare well with the current kinetic rate constants. This method is self consistent and does not have extensive rules. It is first demonstrated and calibrated by computing the HBr reaction from H2 and Br2. This method then is used on other reactions.

Multidimensional Poverty and Health Status as a Predictor of Chronic Income Poverty.

PubMed

Callander, Emily J; Schofield, Deborah J

2015-12-01

Longitudinal analysis of Wave 5 to 10 of the nationally representative Household, Income and Labour Dynamics in Australia dataset was undertaken to assess whether multidimensional poverty status can predict chronic income poverty. Of those who were multidimensionally poor (low income plus poor health or poor health and insufficient education attainment) in 2007, and those who were in income poverty only (no other forms of disadvantage) in 2007, a greater proportion of those in multidimensional poverty continued to be in income poverty for the subsequent 5 years through to 2012. People who were multidimensionally poor in 2007 had 2.17 times the odds of being in income poverty each year through to 2012 than those who were in income poverty only in 2005 (95% CI: 1.23-3.83). Multidimensional poverty measures are a useful tool for policymakers to identify target populations for policies aiming to improve equity and reduce chronic disadvantage. Copyright © 2014 John Wiley & Sons, Ltd.

High-order continuum kinetic method for modeling plasma dynamics in phase space

DOE PAGES

Vogman, G. V.; Colella, P.; Shumlak, U.

2014-12-15

Continuum methods offer a high-fidelity means of simulating plasma kinetics. While computationally intensive, these methods are advantageous because they can be cast in conservation-law form, are not susceptible to noise, and can be implemented using high-order numerical methods. Advances in continuum method capabilities for modeling kinetic phenomena in plasmas require the development of validation tools in higher dimensional phase space and an ability to handle non-cartesian geometries. To that end, a new benchmark for validating Vlasov-Poisson simulations in 3D (x,v x,v y) is presented. The benchmark is based on the Dory-Guest-Harris instability and is successfully used to validate a continuummore » finite volume algorithm. To address challenges associated with non-cartesian geometries, unique features of cylindrical phase space coordinates are described. Preliminary results of continuum kinetic simulations in 4D (r,z,v r,v z) phase space are presented.« less

Critical Evaluation of Kinetic Method Measurements: Possible Origins of Nonlinear Effects

NASA Astrophysics Data System (ADS)

Bourgoin-Voillard, Sandrine; Afonso, Carlos; Lesage, Denis; Zins, Emilie-Laure; Tabet, Jean-Claude; Armentrout, P. B.

2013-03-01

The kinetic method is a widely used approach for the determination of thermochemical data such as proton affinities (PA) and gas-phase acidities ( ΔH° acid ). These data are easily obtained from decompositions of noncovalent heterodimers if care is taken in the choice of the method, references used, and experimental conditions. Previously, several papers have focused on theoretical considerations concerning the nature of the references. Few investigations have been devoted to conditions required to validate the quality of the experimental results. In the present work, we are interested in rationalizing the origin of nonlinear effects that can be obtained with the kinetic method. It is shown that such deviations result from intrinsic properties of the systems investigated but can also be enhanced by artifacts resulting from experimental issues. Overall, it is shown that orthogonal distance regression (ODR) analysis of kinetic method data provides the optimum way of acquiring accurate thermodynamic information.

Simulating Chemical Kinetics Without Differential Equations: A Quantitative Theory Based on Chemical Pathways.

PubMed

Bai, Shirong; Skodje, Rex T

2017-08-17

A new approach is presented for simulating the time-evolution of chemically reactive systems. This method provides an alternative to conventional modeling of mass-action kinetics that involves solving differential equations for the species concentrations. The method presented here avoids the need to solve the rate equations by switching to a representation based on chemical pathways. In the Sum Over Histories Representation (or SOHR) method, any time-dependent kinetic observable, such as concentration, is written as a linear combination of probabilities for chemical pathways leading to a desired outcome. In this work, an iterative method is introduced that allows the time-dependent pathway probabilities to be generated from a knowledge of the elementary rate coefficients, thus avoiding the pitfalls involved in solving the differential equations of kinetics. The method is successfully applied to the model Lotka-Volterra system and to a realistic H 2 combustion model.

From kinetic-structure analysis to engineering crystalline fiber networks in soft materials.

PubMed

Wang, Rong-Yao; Wang, Peng; Li, Jing-Liang; Yuan, Bing; Liu, Yu; Li, Li; Liu, Xiang-Yang

2013-03-07

Understanding the role of kinetics in fiber network microstructure formation is of considerable importance in engineering gel materials to achieve their optimized performances/functionalities. In this work, we present a new approach for kinetic-structure analysis for fibrous gel materials. In this method, kinetic data is acquired using a rheology technique and is analyzed in terms of an extended Dickinson model in which the scaling behaviors of dynamic rheological properties in the gelation process are taken into account. It enables us to extract the structural parameter, i.e. the fractal dimension, of a fibrous gel from the dynamic rheological measurement of the gelation process, and to establish the kinetic-structure relationship suitable for both dilute and concentrated gelling systems. In comparison to the fractal analysis method reported in a previous study, our method is advantageous due to its general validity for a wide range of fractal structures of fibrous gels, from a highly compact network of the spherulitic domains to an open fibrous network structure. With such a kinetic-structure analysis, we can gain a quantitative understanding of the role of kinetic control in engineering the microstructure of the fiber network in gel materials.

Beyond Fourier

NASA Astrophysics Data System (ADS)

Hoch, Jeffrey C.

2017-10-01

Non-Fourier methods of spectrum analysis are gaining traction in NMR spectroscopy, driven by their utility for processing nonuniformly sampled data. These methods afford new opportunities for optimizing experiment time, resolution, and sensitivity of multidimensional NMR experiments, but they also pose significant challenges not encountered with the discrete Fourier transform. A brief history of non-Fourier methods in NMR serves to place different approaches in context. Non-Fourier methods reflect broader trends in the growing importance of computation in NMR, and offer insights for future software development.

MONET: multidimensional radiative cloud scene model

NASA Astrophysics Data System (ADS)

Chervet, Patrick

1999-12-01

All cloud fields exhibit variable structures (bulge) and heterogeneities in water distributions. With the development of multidimensional radiative models by the atmospheric community, it is now possible to describe horizontal heterogeneities of the cloud medium, to study these influences on radiative quantities. We have developed a complete radiative cloud scene generator, called MONET (French acronym for: MOdelisation des Nuages En Tridim.) to compute radiative cloud scene from visible to infrared wavelengths for various viewing and solar conditions, different spatial scales, and various locations on the Earth. MONET is composed of two parts: a cloud medium generator (CSSM -- Cloud Scene Simulation Model) developed by the Air Force Research Laboratory, and a multidimensional radiative code (SHDOM -- Spherical Harmonic Discrete Ordinate Method) developed at the University of Colorado by Evans. MONET computes images for several scenario defined by user inputs: date, location, viewing angles, wavelength, spatial resolution, meteorological conditions (atmospheric profiles, cloud types)... For the same cloud scene, we can output different viewing conditions, or/and various wavelengths. Shadowing effects on clouds or grounds are taken into account. This code is useful to study heterogeneity effects on satellite data for various cloud types and spatial resolutions, and to determine specifications of new imaging sensor.

Use patterns of health information exchange through a multidimensional lens: conceptual framework and empirical validation.

PubMed

Politi, Liran; Codish, Shlomi; Sagy, Iftach; Fink, Lior

2014-12-01

Insights about patterns of system use are often gained through the analysis of system log files, which record the actual behavior of users. In a clinical context, however, few attempts have been made to typify system use through log file analysis. The present study offers a framework for identifying, describing, and discerning among patterns of use of a clinical information retrieval system. We use the session attributes of volume, diversity, granularity, duration, and content to define a multidimensional space in which each specific session can be positioned. We also describe an analytical method for identifying the common archetypes of system use in this multidimensional space. We demonstrate the value of the proposed framework with a log file of the use of a health information exchange (HIE) system by physicians in an emergency department (ED) of a large Israeli hospital. The analysis reveals five distinct patterns of system use, which have yet to be described in the relevant literature. The results of this study have the potential to inform the design of HIE systems for efficient and effective use, thus increasing their contribution to the clinical decision-making process. Copyright © 2014 Elsevier Inc. All rights reserved.

Testlet-Based Multidimensional Adaptive Testing

PubMed Central

Frey, Andreas; Seitz, Nicki-Nils; Brandt, Steffen

2016-01-01

Multidimensional adaptive testing (MAT) is a highly efficient method for the simultaneous measurement of several latent traits. Currently, no psychometrically sound approach is available for the use of MAT in testlet-based tests. Testlets are sets of items sharing a common stimulus such as a graph or a text. They are frequently used in large operational testing programs like TOEFL, PISA, PIRLS, or NAEP. To make MAT accessible for such testing programs, we present a novel combination of MAT with a multidimensional generalization of the random effects testlet model (MAT-MTIRT). MAT-MTIRT compared to non-adaptive testing is examined for several combinations of testlet effect variances (0.0, 0.5, 1.0, and 1.5) and testlet sizes (3, 6, and 9 items) with a simulation study considering three ability dimensions with simple loading structure. MAT-MTIRT outperformed non-adaptive testing regarding the measurement precision of the ability estimates. Further, the measurement precision decreased when testlet effect variances and testlet sizes increased. The suggested combination of the MTIRT model therefore provides a solution to the substantial problems of testlet-based tests while keeping the length of the test within an acceptable range. PMID:27917132

Analysis on the multi-dimensional spectrum of the thrust force for the linear motor feed drive system in machine tools

NASA Astrophysics Data System (ADS)

Yang, Xiaojun; Lu, Dun; Ma, Chengfang; Zhang, Jun; Zhao, Wanhua

2017-01-01

The motor thrust force has lots of harmonic components due to the nonlinearity of drive circuit and motor itself in the linear motor feed drive system. What is more, in the motion process, these thrust force harmonics may vary with the position, velocity, acceleration and load, which affects the displacement fluctuation of the feed drive system. Therefore, in this paper, on the basis of the thrust force spectrum obtained by the Maxwell equation and the electromagnetic energy method, the multi-dimensional variation of each thrust harmonic is analyzed under different motion parameters. Then the model of the servo system is established oriented to the dynamic precision. The influence of the variation of the thrust force spectrum on the displacement fluctuation is discussed. At last the experiments are carried out to verify the theoretical analysis above. It can be found that the thrust harmonics show multi-dimensional spectrum characteristics under different motion parameters and loads, which should be considered to choose the motion parameters and optimize the servo control parameters in the high-speed and high-precision machine tools equipped with the linear motor feed drive system.

Efficient High Order Central Schemes for Multi-Dimensional Hamilton-Jacobi Equations: Talk Slides

NASA Technical Reports Server (NTRS)

Bryson, Steve; Levy, Doron; Biegel, Brian R. (Technical Monitor)

2002-01-01

This viewgraph presentation presents information on the attempt to produce high-order, efficient, central methods that scale well to high dimension. The central philosophy is that the equations should evolve to the point where the data is smooth. This is accomplished by a cyclic pattern of reconstruction, evolution, and re-projection. One dimensional and two dimensional representational methods are detailed, as well.

A method of using cluster analysis to study statistical dependence in multivariate data

NASA Technical Reports Server (NTRS)

Borucki, W. J.; Card, D. H.; Lyle, G. C.

1975-01-01

A technique is presented that uses both cluster analysis and a Monte Carlo significance test of clusters to discover associations between variables in multidimensional data. The method is applied to an example of a noisy function in three-dimensional space, to a sample from a mixture of three bivariate normal distributions, and to the well-known Fisher's Iris data.

Enhancing Student Motivation and Engagement: The Effects of a Multidimensional Intervention

ERIC Educational Resources Information Center

Martin, Andrew J.

2008-01-01

The present study sought to investigate the effects of a multidimensional educational intervention on high school students' motivation and engagement. The intervention incorporated: (a) multidimensional targets of motivation and engagement, (b) empirically derived intervention methodology, (c) research-based risk and protective factors, (d)…

The Impact of Time Perspective Latent Profiles on College Drinking: A Multidimensional Approach

PubMed Central

Braitman, Abby L.; Henson, James M.

2015-01-01

Background Zimbardo and Boyd’s1 time perspective, or the temporal framework individuals use to process information, has been shown to predict health behaviors such as alcohol use. Previous studies supported the predictive validity of individual dimensions of time perspective, with some dimensions acting as protective factors and others as risk factors. However, some studies produced findings contrary to the general body of literature. In addition, time perspective is a multidimensional construct, and the combination of perspectives may be more predictive than individual dimensions in isolation; consequently, multidimensional profiles are a more accurate measure of individual differences and more appropriate for predicting health behaviors. Objectives The current study identified naturally occurring profiles of time perspective and examined their association with risky alcohol use. Methods Data were collected from a college student sample (n = 431, mean age = 20.41 years) using an online survey. Time perspective profiles were identified using latent profile analysis. Results Bootstrapped regression models identified a protective class that engaged in significantly less overall drinking (β = −0.254) as well as engaging in significantly less episodic high risk drinking (β = −0.274). There was also emerging evidence of a high risk time perspective profile that was linked to more overall drinking (β = 0.198) and engaging in more high risk drinking (β = 0.245), though these differences were not significant. Conclusions/Importance These findings support examining time perspective in a multidimensional framework rather than individual dimensions in isolation. Implications include identifying students most in need of interventions, and tailoring interventions to target temporal framing in decision-making. PMID:25607806

Measuring Future Time Perspective across Adulthood: Development and Evaluation of a Brief Multidimensional Questionnaire

PubMed Central

Brothers, Allyson; Chui, Helena; Diehl, Manfred

2014-01-01

Purpose of the Study: Despite calls for the consideration of future time perspective (FTP) as a multidimensional construct, mostly unidimensional measurement instruments have been used. This study had two objectives: (a) to develop a brief multidimensional questionnaire for assessing FTP in adulthood and evaluate its psychometric properties; and (b) to examine age associations and age-group differences of the dimensions of FTP. Design and Methods: Data were collected from 625 community-residing adults between the ages of 18 and 93, representing young, middle-aged, and older adults. The psychometric evaluation involved exploratory factor analyses (EFA) and confirmatory FA (CFA), reliability and validity analyses, and measurement invariance testing. Zero-order and partial correlations were used to examine the association of the dimensions of FTP with age, and multivariate analysis of variance was used to examine age-group differences. Results: EFA and CFA supported a three-factor solution: Future as Open, Future as Limited, and Future as Ambiguous. Metric measurement invariance for this factor structure was confirmed across the three age groups. Reliability and validity analyses provided evidence of sound psychometric properties of the brief questionnaire. Age was negatively associated with Future as Open and positively associated with Future as Limited. Young adults exhibited significantly greater ambiguity toward the future than middle-aged or older adults. Implications: This study provides evidence in support of the psychometric properties of a new brief multidimensional FTP scale. It also provides evidence for a pattern of age associations and age-group differences consistent with life-span developmental theory. PMID:25063938

Development, Content Validity, and User Review of a Web-based Multidimensional Pain Diary for Adolescent and Young Adults With Sickle Cell Disease.

PubMed

Bakshi, Nitya; Stinson, Jennifer N; Ross, Diana; Lukombo, Ines; Mittal, Nonita; Joshi, Saumya V; Belfer, Inna; Krishnamurti, Lakshmanan

2015-06-01

Vaso-occlusive pain, the hallmark of sickle cell disease (SCD), is a major contributor to morbidity, poor health-related quality of life, and health care utilization associated with this disease. There is wide variation in the burden, frequency, and severity of pain experienced by patients with SCD. As compared with health care utilization for pain, a daily pain diary captures the breadth of the pain experience and is a superior measure of pain burden and its impact on patients. Electronic pain diaries based on real-time data capture methods overcome methodological barriers and limitations of paper pain diaries, but their psychometric properties have not been formally established in patients with SCD. To develop and establish the content validity of a web-based multidimensional pain diary for adolescents and young adults with SCD and conduct an end-user review to refine the prototype. Following identification of items, a conceptual model was developed. Interviews with adolescents and young adults with SCD were conducted. Subsequently, end-user review with use of the electronic pain diary prototype was conducted. Two iterative cycles of in-depth cognitive interviews in adolescents and young adults with SCD informed the design and guided the addition, removal, and modification of items in the multidimensional pain diary. Potential end-users provided positive feedback on the design and prototype of the electronic diary. A multidimensional web-based electronic pain diary for adolescents and young adults with SCD has been developed and content validity and initial end-user reviews have been completed.

A second-order accurate kinetic-theory-based method for inviscid compressible flows

NASA Technical Reports Server (NTRS)

Deshpande, Suresh M.

1986-01-01

An upwind method for the numerical solution of the Euler equations is presented. This method, called the kinetic numerical method (KNM), is based on the fact that the Euler equations are moments of the Boltzmann equation of the kinetic theory of gases when the distribution function is Maxwellian. The KNM consists of two phases, the convection phase and the collision phase. The method is unconditionally stable and explicit. It is highly vectorizable and can be easily made total variation diminishing for the distribution function by a suitable choice of the interpolation strategy. The method is applied to a one-dimensional shock-propagation problem and to a two-dimensional shock-reflection problem.

Differential equation methods for simulation of GFP kinetics in non-steady state experiments.

PubMed

Phair, Robert D

2018-03-15

Genetically encoded fluorescent proteins, combined with fluorescence microscopy, are widely used in cell biology to collect kinetic data on intracellular trafficking. Methods for extraction of quantitative information from these data are based on the mathematics of diffusion and tracer kinetics. Current methods, although useful and powerful, depend on the assumption that the cellular system being studied is in a steady state, that is, the assumption that all the molecular concentrations and fluxes are constant for the duration of the experiment. Here, we derive new tracer kinetic analytical methods for non-steady state biological systems by constructing mechanistic nonlinear differential equation models of the underlying cell biological processes and linking them to a separate set of differential equations governing the kinetics of the fluorescent tracer. Linking the two sets of equations is based on a new application of the fundamental tracer principle of indistinguishability and, unlike current methods, supports correct dependence of tracer kinetics on cellular dynamics. This approach thus provides a general mathematical framework for applications of GFP fluorescence microscopy (including photobleaching [FRAP, FLIP] and photoactivation to frequently encountered experimental protocols involving physiological or pharmacological perturbations (e.g., growth factors, neurotransmitters, acute knockouts, inhibitors, hormones, cytokines, and metabolites) that initiate mechanistically informative intracellular transients. When a new steady state is achieved, these methods automatically reduce to classical steady state tracer kinetic analysis. © 2018 Phair. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Non-animal approaches for toxicokinetics in risk evaluations of food chemicals.

PubMed

Punt, Ans; Peijnenburg, Ad A C M; Hoogenboom, Ron L A P; Bouwmeester, Hans

2017-01-01

The objective of the present work was to review the availability and predictive value of non-animal toxicokinetic approaches and to evaluate their current use in European risk evaluations of food contaminants, additives and food contact materials, as well as pesticides and medicines. Results revealed little use of quantitative animal or human kinetic data in risk evaluations of food chemicals, compared with pesticides and medicines. Risk evaluations of medicines provided sufficient in vivo kinetic data from different species to evaluate the predictive value of animal kinetic data for humans. These data showed a relatively poor correlation between the in vivo bioavailability in rats and dogs versus that in humans. In contrast, in vitro (human) kinetic data have been demonstrated to provide adequate predictions of the fate of compounds in humans, using appropriate in vitro-in vivo scalers and by integration of in vitro kinetic data with in silico kinetic modelling. Even though in vitro kinetic data were found to be occasionally included within risk evaluations of food chemicals, particularly results from Caco-2 absorption experiments and in vitro data on gut-microbial conversions, only minor use of in vitro methods for metabolism and quantitative in vitro-in vivo extrapolation methods was identified. Yet, such quantitative predictions are essential in the development of alternatives to animal testing as well as to increase human relevance of toxicological risk evaluations. Future research should aim at further improving and validating quantitative alternative methods for kinetics, thereby increasing regulatory acceptance of non-animal kinetic data.

On Involvement.

ERIC Educational Resources Information Center

Greene, Michael B.

Involvement Ratings In Settings (IRIS), a multi-dimensional non-verbal scale of involvement adaptable to a time-sampling method of data collection, was constructed with the aid of the videotapes of second-grade Follow Through classrooms made by CCEP. Scales were defined through observations of involved and alienated behavior, and the IRIS was…

Video Game Learning Dynamics: Actionable Measures of Multidimensional Learning Trajectories

ERIC Educational Resources Information Center

Reese, Debbie Denise; Tabachnick, Barbara G.; Kosko, Robert E.

2015-01-01

Valid, accessible, reusable methods for instructional video game design and embedded assessment can provide actionable information enhancing individual and collective achievement. Cyberlearning through game-based, metaphor-enhanced learning objects (CyGaMEs) design and embedded assessment quantify player behavior to study knowledge discovery and…

Defining Leadership: Collegiate Women's Learning Circles: A Qualitative Approach

ERIC Educational Resources Information Center

Preston-Cunningham, Tammie; Elbert, Chanda D.; Dooley, Kim E.

2017-01-01

The researchers employed qualitative methods to evaluate first-year female students' definition of "leadership" through involvement in the Women's Learning Circle. The findings revealed that students defined leadership in two dimensions: traits and behaviors. The qualitative findings explore a multidimensional approach to the voices of…

Multi-Dimensional Full Boltzmann-Neutrino-Radiation Hydrodynamic Simulations and Their Detailed Comparisons with Monte-Carlo Methods in Core Collapse Supernovae

NASA Astrophysics Data System (ADS)

Nagakura, H.; Richers, S.; Ott, C. D.; Iwakami, W.; Furusawa, S.; Sumiyoshi, K.; Yamada, S.; Matsufuru, H.; Imakura, A.

2016-10-01

We have developed a 7-dimensional Full Boltzmann-neutrino-radiation-hydrodynamical code and carried out ab-initio axisymmetric CCSNe simulations. I will talk about main results of our simulations and also discuss current ongoing projects.

Extreme Response Style: Which Model Is Best?

ERIC Educational Resources Information Center

Leventhal, Brian

2017-01-01

More robust and rigorous psychometric models, such as multidimensional Item Response Theory models, have been advocated for survey applications. However, item responses may be influenced by construct-irrelevant variance factors such as preferences for extreme response options. Through empirical and simulation methods, this study evaluates the use…

Heteronuclear Multidimensional Protein NMR in a Teaching Laboratory

ERIC Educational Resources Information Center

Wright, Nathan T.

2016-01-01

Heteronuclear multidimensional NMR techniques are commonly used to study protein structure, function, and dynamics, yet they are rarely taught at the undergraduate level. Here, we describe a senior undergraduate laboratory where students collect, process, and analyze heteronuclear multidimensional NMR experiments using an unstudied Ig domain (Ig2…

Compressed Continuous Computation v. 12/20/2016

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gorodetsky, Alex

2017-02-17

A library for performing numerical computation with low-rank functions. The (C3) library enables performing continuous linear and multilinear algebra with multidimensional functions. Common tasks include taking "matrix" decompositions of vector- or matrix-valued functions, approximating multidimensional functions in low-rank format, adding or multiplying functions together, integrating multidimensional functions.

The Discriminating Power of Items that Measure More than One Dimension.

ERIC Educational Resources Information Center

Reckase, Mark D.

The work presented in this paper defined conceptually the concepts of multidimensional discrimination and information, derived mathematical expressions for the concepts for a particular multidimensional item response theory (IRT) model, and applied the concepts to actual test data. Multidimensional discrimination was defined as a function of the…

Multidimensional Computerized Adaptive Testing for Indonesia Junior High School Biology

ERIC Educational Resources Information Center

Kuo, Bor-Chen; Daud, Muslem; Yang, Chih-Wei

2015-01-01

This paper describes a curriculum-based multidimensional computerized adaptive test that was developed for Indonesia junior high school Biology. In adherence to the Indonesian curriculum of different Biology dimensions, 300 items was constructed, and then tested to 2238 students. A multidimensional random coefficients multinomial logit model was…

Supervised and Unsupervised Learning of Multidimensional Acoustic Categories

ERIC Educational Resources Information Center

Goudbeek, Martijn; Swingley, Daniel; Smits, Roel

2009-01-01

Learning to recognize the contrasts of a language-specific phonemic repertoire can be viewed as forming categories in a multidimensional psychophysical space. Research on the learning of distributionally defined visual categories has shown that categories defined over 1 dimension are easy to learn and that learning multidimensional categories is…

Health, Wealth and Wisdom: Exploring Multidimensional Inequality in a Developing Country

ERIC Educational Resources Information Center

Nilsson, Therese

2010-01-01

Despite a broad theoretical literature on multidimensional inequality and a widespread belief that welfare is not synonymous to income--not the least in a developing context--empirical inequality examinations rarely includes several welfare attributes. We explore three techniques on how to evaluate multidimensional inequality using Zambian…

Multidimensional Physical Self-Concept of Athletes with Physical Disabilities

ERIC Educational Resources Information Center

Shapiro, Deborah R.; Martin, Jeffrey J.

2010-01-01

The purposes of this investigation were first to predict reported PA (physical activity) behavior and self-esteem using a multidimensional physical self-concept model and second to describe perceptions of multidimensional physical self-concept (e.g., strength, endurance, sport competence) among athletes with physical disabilities. Athletes (N =…

A Conceptual Model for Multidimensional Analysis of Documents

NASA Astrophysics Data System (ADS)

Ravat, Franck; Teste, Olivier; Tournier, Ronan; Zurlfluh, Gilles

Data warehousing and OLAP are mainly used for the analysis of transactional data. Nowadays, with the evolution of Internet, and the development of semi-structured data exchange format (such as XML), it is possible to consider entire fragments of data such as documents as analysis sources. As a consequence, an adapted multidimensional analysis framework needs to be provided. In this paper, we introduce an OLAP multidimensional conceptual model without facts. This model is based on the unique concept of dimensions and is adapted for multidimensional document analysis. We also provide a set of manipulation operations.

A review of snapshot multidimensional optical imaging: measuring photon tags in parallel

PubMed Central

Gao, Liang; Wang, Lihong V.

2015-01-01

Multidimensional optical imaging has seen remarkable growth in the past decade. Rather than measuring only the two-dimensional spatial distribution of light, as in conventional photography, multidimensional optical imaging captures light in up to nine dimensions, providing unprecedented information about incident photons’ spatial coordinates, emittance angles, wavelength, time, and polarization. Multidimensional optical imaging can be accomplished either by scanning or parallel acquisition. Compared with scanning-based imagers, parallel acquisition—also dubbed snapshot imaging—has a prominent advantage in maximizing optical throughput, particularly when measuring a datacube of high dimensions. Here, we first categorize snapshot multidimensional imagers based on their acquisition and image reconstruction strategies, then highlight the snapshot advantage in the context of optical throughput, and finally we discuss their state-of-the-art implementations and applications. PMID:27134340

A multidimensional subdiffusion model: An arbitrage-free market

NASA Astrophysics Data System (ADS)

Li, Guo-Hua; Zhang, Hong; Luo, Mao-Kang

2012-12-01

To capture the subdiffusive characteristics of financial markets, the subordinated process, directed by the inverse α-stale subordinator Sα(t) for 0 < α < 1, has been employed as the model of asset prices. In this article, we introduce a multidimensional subdiffusion model that has a bond and K correlated stocks. The stock price process is a multidimensional subdiffusion process directed by the inverse α-stable subordinator. This model describes the period of stagnation for each stock and the behavior of the dependency between multiple stocks. Moreover, we derive the multidimensional fractional backward Kolmogorov equation for the subordinated process using the Laplace transform technique. Finally, using a martingale approach, we prove that the multidimensional subdiffusion model is arbitrage-free, and also gives an arbitrage-free pricing rule for contingent claims associated with the martingale measure.

Pseudo second order kinetics and pseudo isotherms for malachite green onto activated carbon: comparison of linear and non-linear regression methods.

PubMed

Kumar, K Vasanth; Sivanesan, S

2006-08-25

Pseudo second order kinetic expressions of Ho, Sobkowsk and Czerwinski, Blanachard et al. and Ritchie were fitted to the experimental kinetic data of malachite green onto activated carbon by non-linear and linear method. Non-linear method was found to be a better way of obtaining the parameters involved in the second order rate kinetic expressions. Both linear and non-linear regression showed that the Sobkowsk and Czerwinski and Ritchie's pseudo second order model were the same. Non-linear regression analysis showed that both Blanachard et al. and Ho have similar ideas on the pseudo second order model but with different assumptions. The best fit of experimental data in Ho's pseudo second order expression by linear and non-linear regression method showed that Ho pseudo second order model was a better kinetic expression when compared to other pseudo second order kinetic expressions. The amount of dye adsorbed at equilibrium, q(e), was predicted from Ho pseudo second order expression and were fitted to the Langmuir, Freundlich and Redlich Peterson expressions by both linear and non-linear method to obtain the pseudo isotherms. The best fitting pseudo isotherm was found to be the Langmuir and Redlich Peterson isotherm. Redlich Peterson is a special case of Langmuir when the constant g equals unity.

The Space-Time Conservation Element and Solution Element Method: A New High-Resolution and Genuinely Multidimensional Paradigm for Solving Conservation Laws. 1; The Two Dimensional Time Marching Schemes

NASA Technical Reports Server (NTRS)

Chang, Sin-Chung; Wang, Xiao-Yen; Chow, Chuen-Yen

1998-01-01

A new high resolution and genuinely multidimensional numerical method for solving conservation laws is being, developed. It was designed to avoid the limitations of the traditional methods. and was built from round zero with extensive physics considerations. Nevertheless, its foundation is mathmatically simple enough that one can build from it a coherent, robust. efficient and accurate numerical framework. Two basic beliefs that set the new method apart from the established methods are at the core of its development. The first belief is that, in order to capture physics more efficiently and realistically, the modeling, focus should be placed on the original integral form of the physical conservation laws, rather than the differential form. The latter form follows from the integral form under the additional assumption that the physical solution is smooth, an assumption that is difficult to realize numerically in a region of rapid chance. such as a boundary layer or a shock. The second belief is that, with proper modeling of the integral and differential forms themselves, the resulting, numerical solution should automatically be consistent with the properties derived front the integral and differential forms, e.g., the jump conditions across a shock and the properties of characteristics. Therefore a much simpler and more robust method can be developed by not using the above derived properties explicitly.

Development of achiral and chiral 2D HPLC methods for analysis of albendazole metabolites in microsomal fractions using multivariate analysis for the in vitro metabolism.

PubMed

Belaz, Kátia Roberta A; Pereira-Filho, Edenir Rodrigues; Oliveira, Regina V

2013-08-01

In this work, the development of two multidimensional liquid chromatography methods coupled to a fluorescence detector is described for direct analysis of microsomal fractions obtained from rat livers. The chiral multidimensional method was then applied for the optimization of the in vitro metabolism of albendazole by experimental design. Albendazole was selected as a model drug because of its anthelmintics properties and recent potential for cancer treatment. The development of two fully automated achiral-chiral and chiral-chiral high performance liquid chromatography (HPLC) methods for the determination of albendazole (ABZ) and its metabolites albendazole sulphoxide (ABZ-SO), albendazole sulphone (ABZ-SO2) and albendazole 2-aminosulphone (ABZ-SO2NH2) in microsomal fractions are described. These methods involve the use of a phenyl (RAM-phenyl-BSA) or octyl (RAM-C8-BSA) restricted access media bovine serum albumin column for the sample clean-up, followed by an achiral phenyl column (15.0×0.46cmI.D.) or a chiral amylose tris(3,5-dimethylphenylcarbamate) column (15.0×0.46cmI.D.). The chiral 2D HPLC method was applied to the development of a compromise condition for the in vitro metabolism of ABZ by means of experimental design involving multivariate analysis. Copyright © 2013 Elsevier B.V. All rights reserved.